Medical Image Computing and Computer Assisted Intervention − MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part I

Medical Image Synthesis with Context-Aware Generative Adversarial Networks

Nie, D., Trullo, R., Lian, J., Petitjean, C., Ruan, S., Wang, Q., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_48 · Cited by 751 · see citing works

Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation

Yang, L., Zhang, Y., Chen, J., Zhang, S., & Chen, D. Z. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_46 · Cited by 526 · see citing works

Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation

Bai, W., Oktay, O., Sinclair, M. D., Suzuki, H., Rajchl, M., Tarroni, G., Glocker, B., King, A. P., Matthews, P. M., & Rueckert, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_29 · Cited by 480 · see citing works

Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images

Zhang, Y., Yang, L., Chen, J., Fredericksen, M., Hughes, D. P., & Chen, D. Z. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_47 · Cited by 452 · see citing works

Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks

Ding, J., Li, A., Hu, Z., & Wang, L. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66179-7_64 · Cited by 385 · see citing works

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Ghafoorian, M., Mehrtash, A., Kapur, T., Karssemeijer, N., Marchiori, E., Pesteie, M., Guttmann, C. R. G., de Leeuw, F., Tempany, C. M., van Ginneken, B., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_59 · Cited by 337 · see citing works

Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection

Wang, Z., Yin, Y., Shi, J., Fang, W., Li, H., & Wang, X. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_31 · Cited by 318 · see citing works

A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans

Zhou, Y., Xie, L., Shen, W., Wang, Y., Fishman, E. K., & Yuille, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_79 · Cited by 310 · see citing works

Spectral Graph Convolutions for Population-Based Disease Prediction

Parisot, S., Ktena, S. I., Ferrante, E., Lee, M., Moreno, R. G., Glocker, B., & Rueckert, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_21 · Cited by 260 · see citing works

Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification

Zhu, W., Lou, Q., Vang, Y. S., & Xie, X. S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_69 · Cited by 251 · see citing works

Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

Yang, D., Xu, D., Zhou, S. K., Georgescu, B., Chen, M., Grbić, S., Metaxas, D., & Comaniciu, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_58 · Cited by 233 · see citing works

Robust non-rigid registration through agent-based action learning

Krebs, J., Mansi, T., Delingette, H., Zhang, L., Ghesu, F. C., Miao, S., Maier, A. K., Ayache, N., Liao, R., & Kamen, A. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66182-7_40 · Cited by 225 · see citing works

Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets

Yu, L., Cheng, J.-Z., Dou, Q., Yang, X., Chen, H., Qin, J., & Heng, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_33 · Cited by 218 · see citing works

Lesion Detection and Grading of Diabetic Retinopathy via Two-Stages Deep Convolutional Neural Networks

Yang, Y., Li, T., Li, W., Wu, H., Fan, W., & Zhang, W. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_61 · Cited by 211 · see citing works

Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks

Ktena, S. I., Parisot, S., Ferrante, E., Rajchl, M., Lee, M., Glocker, B., & Rueckert, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_54 · Cited by 196 · see citing works

Concurrent Segmentation and Localization for Tracking of Surgical Instruments

Laina, I., Rieke, N., Rupprecht, C., Vizcaíno, J. P., Eslami, A., Tombari, F., & Navab, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_75 · Cited by 165 · see citing works

Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules

Feng, X., Yang, J., Laine, A. F., & Angelini, E. D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_65 · Cited by 165 · see citing works

Automated Pulmonary Nodule Detection via 3D ConvNets with Online Sample Filtering and Hybrid-Loss Residual Learning

Dou, Q., Chen, H., Jin, Y., Lin, H., Qin, J., & Heng, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_72 · Cited by 156 · see citing works

Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution

Tanno, R., Worrall, D. E., Ghosh, A., Kaden, E., Sotiropoulos, S. N., Criminisi, A., & Alexander, D. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_70 · Cited by 146 · see citing works

Skin Disease Recognition Using Deep Saliency Features and Multimodal Learning of Dermoscopy and Clinical Images

Ge, Z., Demyanov, S., Chakravorty, R., Bowling, A., & Garnavi, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_29 · Cited by 145 · see citing works

Progressive and Multi-path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images

Harrison, A. P., Xu, Z., George, K., Lu, L., Summers, R. M., & Mollura, D. J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_71 · Cited by 129 · see citing works

Semi-supervised Deep Learning for Fully Convolutional Networks

Baur, C., Albarqouni, S., & Navab, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_36 · Cited by 127 · see citing works

Boundary-Aware Fully Convolutional Network for Brain Tumor Segmentation

Shen, H., Wang, R., Zhang, J., & McKenna, S. J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_49 · Cited by 110 · see citing works

Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI

Maicas, G., Carneiro, G., Bradley, A. P., Nascimento, J. C., & Reid, I. D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_76 · Cited by 109 · see citing works

Deep Supervision for Pancreatic Cyst Segmentation in Abdominal CT Scans

Zhou, Y., Xie, L., Fishman, E. K., & Yuille, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_26 · Cited by 102 · see citing works

Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy

Ambrosini, P., Ruijters, D., Niessen, W. J., Moelker, A., & van Walsum, T. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66185-8_65 · Cited by 102 · see citing works

Deep Correlational Learning for Survival Prediction from Multi-modality Data

Yao, J., Zhu, X., Zhu, F., & Huang, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_46 · Cited by 102 · see citing works

Pathological OCT Retinal Layer Segmentation Using Branch Residual U-Shape Networks

Apostolopoulos, S., Zanet, S. I. D., Ciller, C., Wolf, S., & Sznitman, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_34 · Cited by 101 · see citing works

SD-Layer: Stain Deconvolutional Layer for CNNs in Medical Microscopic Imaging

Duggal, R., Gupta, A., Gupta, R., & Mallick, P. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66179-7_50 · Cited by 99 · see citing works

Image Super Resolution Using Generative Adversarial Networks and Local Saliency Maps for Retinal Image Analysis

Mahapatra, D., Bozorgtabar, B., Hewavitharanage, S., & Garnavi, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_44 · Cited by 96 · see citing works

Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data

Roy, A. G., Conjeti, S., Sheet, D., Katouzian, A., Navab, N., & Wachinger, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_27 · Cited by 95 · see citing works

Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery

Kurmann, T., Neila, P. M., Du, X., Fua, P., Stoyanov, D. V., Wolf, S., & Sznitman, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_57 · Cited by 92 · see citing works

Transferable Multi-model Ensemble for Benign-Malignant Lung Nodule Classification on Chest CT

Xie, Y., Xia, Y., Zhang, J., Feng, D. D., FULHAM, M. J., & Cai, W. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_75 · Cited by 76 · see citing works

Robust Multi-modal MR Image Synthesis

Joyce, T., Chartsias, A., & Tsaftaris, S. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_40 · Cited by 72 · see citing works

Classification of Pancreatic Cysts in Computed Tomography Images Using a Random Forest and Convolutional Neural Network Ensemble

Dmitriev, K., Kaufman, A. E., Javed, A. A., Hruban, R. H., Fishman, E. K., Lennon, A. M., & Saltz, J. H. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_18 · Cited by 71 · see citing works

TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References

Zhang, Z., Chen, P., Sapkota, M., & Yang, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_37 · Cited by 71 · see citing works

Isotropic Reconstruction of 3D Fluorescence Microscopy Images Using Convolutional Neural Networks

WEIGERT, M. G., Royer, L. A., Jug, F., & Myers, E. W. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_15 · Cited by 69 · see citing works

Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoder

Sedai, S., Mahapatra, D., Hewavitharanage, S., Maetschke, S., & Garnavi, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_9 · Cited by 69 · see citing works

Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion

Hou, B., Alansary, A., McDonagh, S., Davidson, A., Rutherford, M., Hajnal, J. V., Rueckert, D., Glocker, B., & Kainz, B. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66185-8_34 · Cited by 68 · see citing works

Full Quantification of Left Ventricle via Deep Multitask Learning Network Respecting Intra- and Inter-Task Relatedness

Xue, W., Lum, A., Mercado, A., Landis, M. S., Warrington, J. C., & Li, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_32 · Cited by 66 · see citing works

Towards Automatic Semantic Segmentation in Volumetric Ultrasound

Yang, X., Yu, L., Li, S., Wang, X., Wang, N., Qin, J., Ni, D., & Heng, P.-A. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66182-7_81 · Cited by 61 · see citing works

Towards Image-Guided Pancreas and Biliary Endoscopy: Automatic Multi-organ Segmentation on Abdominal CT with Dense Dilated Networks

Gibson, E., Giganti, F., Hu, Y., Bonmati, E., Bandula, S., Gurusamy, K. S., Davidson, B. R., Pereira, S. P., Clarkson, M. J., & Barratt, D. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_83 · Cited by 61 · see citing works

Scalable Multimodal Convolutional Networks for Brain Tumour Segmentation

Fidon, L., Li, W., Garcia-Peraza-Herrera, L. C., Ekanayake, J., Kitchen, N., Ourselin, S., & Vercauteren, T. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66179-7_33 · Cited by 60 · see citing works

Deep Multi-task Multi-channel Learning for Joint Classification and Regression of Brain Status

Liu, M., Zhang, J., Adeli, E., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_1 · Cited by 57 · see citing works

Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization by Context-Guided Fully Convolutional Networks

Zhang, J., Liu, M., Wang, L., Chen, S., Yuan, P., Li, J., Shen, S. G.-F., Tang, Z., Chen, K.-C., Xia, J. J., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_81 · Cited by 54 · see citing works

Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels)

Gu, L., Zheng, Y., Bise, R., Sato, I., Imanishi, N., & Aiso, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_80 · Cited by 49 · see citing works

Deep Neural Networks Predict Remaining Surgery Duration from Cholecystectomy Videos

Aksamentov, I., Twinanda, A. P., Mutter, D., Marescaux, J., & Padoy, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_66 · Cited by 48 · see citing works

Tracking and Segmentation of the Airways in Chest CT Using a Fully Convolutional Network

Meng, Q., Roth, H. R., Kitasaka, T., Oda, M., Ueno, J., & Mori, K. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_23 · Cited by 48 · see citing works

Supervised Intra-embedding of Fisher Vectors for Histopathology Image Classification

Song, Y., Chang, H., Huang, H., & Cai, W. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_12 · Cited by 46 · see citing works

Deep Learning for Isotropic Super-Resolution from Non-isotropic 3D Electron Microscopy

Heinrich, L., Bogovic, J., & Saalfeld, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_16 · Cited by 45 · see citing works

CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance

Jesson, A., Guizard, N., Ghalehjegh, S. H., Goblot, D., Soudan, F., & Chapados, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_73 · Cited by 45 · see citing works

Deep Learning for Sensorless 3D Freehand Ultrasound Imaging

Prevost, R., Salehi, M., Sprung, J., Ladikos, A., Bauer, R., & Wein, W. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_71 · Cited by 43 · see citing works

Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes

Abdi, A. H., Luong, C. L., Tsang, T. S. M., Jue, J., Gin, K., Yeung, D. F., Hawley, D., Rohling, R. N., & Abolmaesumi, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_35 · Cited by 43 · see citing works

Temporal HeartNet: Towards Human-Level Automatic Analysis of Fetal Cardiac Screening Video

Huang, W., Bridge, C. P., Noble, J. A., & Zisserman, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_39 · Cited by 43 · see citing works

GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network

Dubost, F., Bortsova, G., Adams, H. H. H., Ikram, M. A., Niessen, W. J., Vernooij, M. W., & de Bruijne, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_25 · Cited by 42 · see citing works

Precise Ultrasound Bone Registration with Learning-Based Segmentation and Speed of Sound Calibration

Salehi, M., Prevost, R., Moctezuma, J.-L., Navab, N., & Wein, W. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_77 · Cited by 42 · see citing works

Pancreas Segmentation in MRI Using Graph-Based Decision Fusion on Convolutional Neural Networks

Cai, J., Lü, L., Xie, Y., Xing, F., & Yang, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_77 · Cited by 42 · see citing works

Clinical Target-Volume Delineation in Prostate Brachytherapy Using Residual Neural Networks

Anas, E. M. A., Nouranian, S., Mahdavi, S. S., Spadinger, I., Morris, W. J., Salcudean, S. E., Mousavi, P., & Abolmaesumi, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_42 · Cited by 40 · see citing works

Direct Detection of Pixel-Level Myocardial Infarction Areas via a Deep-Learning Algorithm

Xu, C., Xu, L., Gao, Z., Zhao, S., Zhang, H., Zhang, Y., Du, X., Zhao, S. G., Ghista, D. N., & Li, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_28 · Cited by 39 · see citing works

Detection and Characterization of the Fetal Heartbeat in Free-hand Ultrasound Sweeps with Weakly-supervised Two-streams Convolutional Networks

Gao, Y., & Noble, J. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_35 · Cited by 37 · see citing works

DARWIN: Deformable Patient Avatar Representation With Deep Image Network

Singh, V. K., Ma, K., Tamersoy, B., Chang, Y., Wimmer, A., O’Donnell, T., & Chen, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_56 · Cited by 37 · see citing works

Automatic Quality Control of Cardiac MRI Segmentation in Large-Scale Population Imaging

Robinson, R., Valindria, V. V., Bai, W., Suzuki, H., Matthews, P. M., Page, C., Rueckert, D., & Glocker, B. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66182-7_82 · Cited by 37 · see citing works

Boundary Regularized Convolutional Neural Network for Layer Parsing of Breast Anatomy in Automated Whole Breast Ultrasound

Bian, C., Lee, R., Chou, Y., & Cheng, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_30 · Cited by 35 · see citing works

Physiological Parameter Estimation from Multispectral Images Unleashed

Wirkert, S., Vemuri, A., Kenngott, H., Moccia, S., GOETZ, M. A., Mayer, B. F. B., Maier-Hein, K. H., Elson, D. S., & Maier‐Hein, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_16 · Cited by 35 · see citing works

Deep Convolutional Encoder-Decoders for Prostate Cancer Detection and Classification

Kiraly, A. P., Nader, C. A., Tüysüzoğlu, A., Grimm, R., Kiefer, B., El-Zehiry, N. Y., & Kamen, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_56 · Cited by 34 · see citing works

Deep Image-to-Image Recurrent Network with Shape Basis Learning for Automatic Vertebra Labeling in Large-Scale 3D CT Volumes

Yang, D., Xiong, T., Xu, D., Zhou, S. K., Xu, Z., Chen, M., Park, J., Grbić, S., Tran, T. D., Chin, P. S., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_57 · Cited by 33 · see citing works

Retinal Microaneurysm Detection Using Clinical Report Guided Multi-sieving CNN

Dai, L., Sheng, B., Wu, Q. E., Li, H., Hou, X., Jia, W., & Fang, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_60 · Cited by 32 · see citing works

Classification of Major Depressive Disorder via Multi-site Weighted LASSO Model

Zhu, D., Riedel, B. C., Jahanshad, N., Groenewold, N. A., Stein, D. J., Gotlib, I. H., Sacchet, M. D., Dima, D., Cole, J. H., Fu, C. H. Y., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_19 · Cited by 31 · see citing works

X-Ray In-Depth Decomposition: Revealing the Latent Structures

Albarqouni, S., Fotouhi, J., & Navab, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_51 · Cited by 29 · see citing works

Joint Reconstruction and Segmentation of 7T-like MR Images from 3T MRI Based on Cascaded Convolutional Neural Networks

Bahrami, K., Rekik, I., Shi, F., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_87 · Cited by 29 · see citing works

Maximum Mean Discrepancy Based Multiple Kernel Learning for Incomplete Multimodality Neuroimaging Data

Zhu, X., Thung, K., Adeli, E., Zhang, Y., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_9 · Cited by 29 · see citing works

Improving Needle Detection in 3D Ultrasound Using Orthogonal-Plane Convolutional Networks

Pourtaherian, A., Zanjani, F. G., Zinger, S., Mihajlović, N., Ng, G. C., Korsten, H. H. M., & de With, P. H. N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_69 · Cited by 28 · see citing works

Joint Detection and Diagnosis of Prostate Cancer in Multi-parametric MRI Based on Multimodal Convolutional Neural Networks

Yang, X. Y., Wang, Z., Liu, C., Le, H. M., Chen, J., Cheng, K.-T. T., & Wang, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_49 · Cited by 28 · see citing works

Hashing with Residual Networks for Image Retrieval

Conjeti, S., Roy, A. G., Katouzian, A., & Navab, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_62 · Cited by 28 · see citing works

Hybrid Mass Detection in Breast MRI Combining Unsupervised Saliency Analysis and Deep Learning

Amit, G., Hadad, O., Alpert, S., Tlusty, T., Gur, Y., Ben‐Ari, R., & Hashoul, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_68 · Cited by 27 · see citing works

Deep Multiple Instance Hashing for Scalable Medical Image Retrieval

Conjeti, S., Paschali, M., Katouzian, A., & Navab, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_63 · Cited by 27 · see citing works

Holistic Segmentation of Intermuscular Adipose Tissues on Thigh MRI

Yao, J., Kovacs, W. C., Hsieh, N., Liu, C., & Summers, R. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_84 · Cited by 27 · see citing works

BRIEFnet: Deep Pancreas Segmentation Using Binary Sparse Convolutions

Heinrich‬, M. P., & Oktay, O. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_38 · Cited by 26 · see citing works

Fully Automated Segmentation-Based Respiratory Motion Correction of Multiplanar Cardiac Magnetic Resonance Images for Large-Scale Datasets

Sinclair, M. D., Bai, W., Anton, E. P., Oktay, O., Rueckert, D., & King, A. P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_38 · Cited by 26 · see citing works

Ultrasonic Needle Tracking with a Fibre-Optic Ultrasound Transmitter for Guidance of Minimally Invasive Fetal Surgery

Xia, W., Noimark, S., Sebastien Ourselin, A., West, S. J., Finlay, M., David, A. L., & Desjardins, A. E. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_72 · Cited by 25 · see citing works

Segmentation-Free Kidney Localization and Volume Estimation Using Aggregated Orthogonal Decision CNNs

Hussain, M. A., Amir-Khalili, A., Hamarneh, G., & Rafeef Abugharbieh, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_70 · Cited by 25 · see citing works

Gray Matter Surface Based Spatial Statistics (GS-BSS) in Diffusion Microstructure

Parvathaneni, P., Rogers, B. P., Huo, Y., Schilling, K. G., Hainline, A. E., Anderson, A. W., Woodward, N. D., & Landman, B. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_73 · Cited by 24 · see citing works

BRANCH:Bifurcation Recognition for Airway Navigation based on struCtural cHaracteristics

Shen, M., Giannarou, S., Shah, P. L., & Yang, G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_21 · Cited by 24 · see citing works

Quantification of Metabolites in Magnetic Resonance Spectroscopic Imaging Using Machine Learning

Das, D., Coello, E., Schulte, R. F., & Menze, B. H. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_53 · Cited by 23 · see citing works

Retrospective Head Motion Estimation in Structural Brain MRI with 3D CNNs

Iglesias, J. E., Lerma‐Usabiaga, G., García-Peraza-Herrera, L. C., Martinez, S., & Paz‐Alonso, P. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_36 · Cited by 22 · see citing works

Online Statistical Inference for Large-Scale Binary Images

Chung, M. K., Chuang, Y. J., & Vorperian, H. K. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_82 · Cited by 22 · see citing works

DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI

Huang, Y., Shao, L., & Frangi, A. F. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_11 · Cited by 21 · see citing works

Learning CNNs with Pairwise Domain Adaption for Real-Time 6DoF Ultrasound Transducer Detection and Tracking from X-Ray Images

Zheng, J., Miao, S., & Liao, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_73 · Cited by 21 · see citing works

Using Convolutional Neural Networks to Automatically Detect Eye-Blink Artifacts in Magnetoencephalography Without Resorting to Electrooculography

Garg, P., Davenport, E. M., Murugesan, G. K., Wagner, B. C., Whitlow, C. T., Maldjian, J. A., & Montillo, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_43 · Cited by 21 · see citing works

Does Manual Delineation only Provide the Side Information in CT Prostate Segmentation?

Shi, Y., Yang, W., Gao, Y., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_79 · Cited by 21 · see citing works

A Submodular Approach to Create Individualized Parcellations of the Human Brain

Salehi, M., Karbasi, A., Scheinost, D., & Constable, R. T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_55 · Cited by 21 · see citing works

Supervised Action Classifier: Approaching Landmark Detection as Image Partitioning

Xu, Z., Huang, Q., Park, J., Chen, M., Xu, D., Yang, D., Liu, D. S., & Zhou, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_39 · Cited by 20 · see citing works

Neuron Segmentation Using Deep Complete Bipartite Networks

Chen, J., Banerjee, S., Grama, A., Scheirer, W. J., & Chen, D. Z. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_3 · Cited by 20 · see citing works

Kernel Generalized-Gaussian Mixture Model for Robust Abnormality Detection

Kumar, N. A., Rajwade, A. V., Chandran, S., & Awate, S. P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_3 · Cited by 19 · see citing works

Personalized Diagnosis for Alzheimer’s Disease

Zhu, Y., Kim, M., Zhu, X., Yan, J. H., Kaufer, D., & Guorong Wu, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_24 · Cited by 19 · see citing works

Personalized Pancreatic Tumor Growth Prediction via Group Learning

Zhang, L., Lü, L., Summers, R. M., Kebebew, E., & Yao, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_48 · Cited by 19 · see citing works

Unbiased Shape Compactness for Segmentation

Dolz, J., Ayed, I. B., & Desrosiers, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_86 · Cited by 18 · see citing works

Endoscopic Depth Measurement and Super-Spectral-Resolution Imaging

Lin, J., Clancy, N. T., Hu, Y., Qi, J., Tatla, T. S., Stoyanov, D. V., Maier‐Hein, L., & Elson, D. S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_5 · Cited by 18 · see citing works

Flow Network Based Cardiac Motion Tracking Leveraging Learned Feature Matching

Parajuli, N., Lu, A., Stendahl, J. C., Zontak, M., Boutagy, N. E., Alkhalil, I., Eberle, M. M., Lin, B. A., O’Donnell, M., Sinusas, A. J., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_32 · Cited by 18 · see citing works

Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks

Koval, I., Schiratti, J.-B., Routier, A., Bacci, M., Colliot, O., Allassonnière, S., & Durrleman, S. (2017) · HAL · Cited by 18 · see citing works

Convolutional Neural Network and In-Painting Techniques for the Automatic Assessment of Scoliotic Spine Surgery from Biplanar Radiographs

Aubert, B., Vidal, P. A., Stefan Parent, D., Cresson, T., Vázquez, C., & de Guise, J. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_78 · Cited by 17 · see citing works

Unsupervised Feature Learning for Endomicroscopy Image Retrieval

Gu, Y., Vyas, K., Yang, J., & Yang, G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_8 · Cited by 17 · see citing works

Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks

Hu, Y., Gibson, E., Vercauteren, T., Emberton, M., Ahmed, H. U., Moore, C. M., Vercauteren, T. K., & Hu, Y. (2017) · UCL Discovery (University College London) · Cited by 17 · see citing works

Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks

Bortsova, G., van Tulder, G., Dubost, F., Peng, T., Navab, N., van der Lugt, A., Bos, D., & de Bruijne, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_41 · Cited by 15 · see citing works

Image-Driven Stochastic Identification of Boundary Conditions for Predictive Simulation

Peterlík, I., Haouchine, N., Ručka, L., & Cotin, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_62 · Cited by 15 · see citing works

Compresso: Efficient Compression of Segmentation Data for Connectomics

Matejek, B., Haehn, D., Lekschas, F., Mitzenmacher, M., & Pfister, H. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_89 · Cited by 15 · see citing works

Automatic Labeling of Vascular Structures with Topological Constraints via HMM

Wang, X., Liu, Y., Wu, Z., Mou, X., Zhou, M., Ballester, M. Á. G., & Zhang, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_24 · Cited by 15 · see citing works

Surgical Soundtracks: Towards Automatic Musical Augmentation of Surgical Procedures

Matinfar, S., Nasseri, M. A., Eck, U., Roodaki, H., Navab, N., Lohmann, C. P., Maier, M. M., & Navab, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_76 · Cited by 15 · see citing works

GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction

Sun, X., Hu, L., Yao, Y., & Wang, Y. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_13 · Cited by 14 · see citing works

Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recovery

Haeffele, B. D., Stahl, R. J., Vanmeerbeeck, G., & Vidal, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_13 · Cited by 14 · see citing works

Neighborhood Matching for Curved Domains with Application to Denoising in Diffusion MRI

Chen, G., Dong, B., Zhang, Y., Shen, D. G., & Yap, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_72 · Cited by 14 · see citing works

Tracking the Aortic Lumen Geometry by Optimizing the 3D Orientation of Its Cross-sections

Álvarez, L., Trujillo, A., Cuenca, C., González, E., Esclarín, J., Gómez, L., Mazorra, L., Alemán-Flores, M., Tahoces, P. G., & Carreira, J. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_20 · Cited by 14 · see citing works

Motion-Compensated Autonomous Scanning for Tumour Localisation Using Intraoperative Ultrasound

Zhang, L., Ye, M., Giannarou, S., Pratt, P., & Yang, G.-Z. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_70 · Cited by 13 · see citing works

Segmentation of Cortical and Subcortical Multiple Sclerosis Lesions Based on Constrained Partial Volume Modeling

Fartaria, M. J., Roche, A., Meuli, R. A., Granziera, C., Kober, T., & Cuadra, M. B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_17 · Cited by 13 · see citing works

Cell Lineage Tracing in Lens-Free Microscopy Videos

Rempfler, M., Kumar, S., Stierle, V., Paulitschke, P., Andres, B., & Menze, B. H. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_1 · Cited by 13 · see citing works

A Localized Statistical Motion Model as a Reproducing Kernel for Non-rigid Image Registration

Jud, C., Giger, A., Sandkühler, R., & Cattin, P. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_30 · Cited by 13 · see citing works

Fast Prospective Detection of Contrast Inflow in X-ray Angiograms with Convolutional Neural Network and Recurrent Neural Network

Ma, H., Ambrosini, P., & van Walsum, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_52 · Cited by 13 · see citing works

Multi-label Inductive Matrix Completion for Joint MGMT and IDH1 Status Prediction for Glioma Patients

Chen, L., Zhang, H., Thung, K., Liu, L., Lu, J., Wu, J., Wang, Q., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_51 · Cited by 13 · see citing works

An Approach for Needle Based Optical Coherence Elastography Measurements

Latus, S., Otte, C., Schlüter, M., Rehra, J., Bizon, K., Schulz‐Hildebrandt, H., Saathoff, T., Hüttmann, G., & Schlaefer, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_74 · Cited by 13 · see citing works

A Time Saver: Optimization Approach for the Fully Automatic 3D Planning of Forearm Osteotomies

Carrillo, F., Vlachopoulos, L., Schweizer, A., Nagy, L., Snedeker, J. G., & Fürnstahl, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_55 · Cited by 12 · see citing works

Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis

Prasanna, P., Jhimli Mitra, A., Beig, N. G., Partovi, S., Singh, G., Pinho, M. C., Madabhushi, A., & Tiwari, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_52 · Cited by 12 · see citing works

Revealing Hidden Potentials of the q-Space Signal in Breast Cancer

Jäger, P. F., Bickelhaupt, S., Laun, F. B., Lederer, W., Heidi, D., Kuder, T. A., Paech, D., Bonekamp, D., Radbruch, A., Delorme, S., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_76 · Cited by 12 · see citing works

QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

Schirrmacher, F., Köhler, T., Husvogt, L., Fujimoto, J. G., Joachim Hornegger, A., & Maier, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_10 · Cited by 11 · see citing works

Cell Encoding for Histopathology Image Classification

Shi, X., Xing, F., Xie, Y., Su, H., & Yang, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_4 · Cited by 11 · see citing works

Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients Using a Bag-of-Lesions Brain Representation

Doyle, A., Precup, D., Arnold, D. L., & Arbel, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_22 · Cited by 11 · see citing works

Providing Effective Real-Time Feedback in Simulation-Based Surgical Training

Ma, X., Wijewickrema, S. N. R., Zhou, Y., Zhou, S., O’Leary, S. J., & Bailey, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_64 · Cited by 11 · see citing works

Building Disease Detection Algorithms with Very Small Numbers of Positive Samples

Wong, K. C. L., Karargyris, A., Syeda-Mahmood, T. F., & Moradi, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_54 · Cited by 11 · see citing works

DejaVu: Intra-operative Simulation for Surgical Gesture Rehearsal

Haouchine, N., Stoyanov, D. V., Roy, F., & Cotin, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_59 · Cited by 10 · see citing works

CT Image Enhancement for Feature Detection and Localization

Nardelli, P., Ross, J. C., & Estépar, R. S. J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_26 · Cited by 10 · see citing works

Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis

Yoo, Y., Tang, L. Y. W., Kim, S., Kim, H. J., Lee, L. E., Li, D. K. B., Kolind, S., Traboulsee, A. L., & Tam, R. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_55 · Cited by 10 · see citing works

Histological Detection of High-Risk Benign Breast Lesions from Whole Slide Images

Tosun, A. B., Nguyen, L., Ong, N., Navolotskaia, O., Carter, G. J., Fine, J. L., Taylor, D. L., & Chennubhotla, S. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_17 · Cited by 10 · see citing works

Temporal Interpolation of Abdominal MRIs Acquired During Free-Breathing

Karani, N., Tanner, C., Kozerke, S., & Ender Konukoglu, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_41 · Cited by 10 · see citing works

Toward Computer-Assisted Planning for Interstitial Laser Ablation of Malignant Brain Tumors Using a Tubular Continuum Robot

Granna, J., Nabavi, A., & Burgner-Kahrs, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_63 · Cited by 9 · see citing works

A Multi-atlas Approach to Region of Interest Detection for Medical Image Classification

Wang, H., Moradi, M., Gur, Y., Prasanna, P. M., & Syeda-Mahmood, T. F. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_20 · Cited by 9 · see citing works

Groupwise Registration of MR Brain Images Containing Tumors via Spatially Constrained Low-Rank Based Image Recovery

Tang, Z., Cui, Y., & Jiang, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_45 · Cited by 9 · see citing works

Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images

Pouch, A. M., Aly, A. H., Lai, E. K., Yushkevich, N., Stoffers, R. H., Gorman, J. H., Cheung, A. T., Gorman, J. H., Gorman, R. C., & Yushkevich, P. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_85 · Cited by 9 · see citing works

Analysis of Periodicity in Video Sequences Through Dynamic Linear Modeling

McLeod, A. J., Capaldi, D. P. I., Baxter, J. S. H., Párraga, G., Luó, X., & Peters, T. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_44 · Cited by 9 · see citing works

Learning-Based Spatiotemporal Regularization and Integration of Tracking Methods for Regional 4D Cardiac Deformation Analysis

Lu, A., Zontak, M., Parajuli, N., Stendahl, J. C., Boutagy, N. E., Eberle, M. M., Alkhalil, I., O’Donnell, M., Sinusas, A. J., & Duncan, J. S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_37 · Cited by 9 · see citing works

A Variational Approach to Sparse Model Error Estimation in Cardiac Electrophysiological Imaging

Ghimire, S., Sapp, J. L., Horacek, M., & Wang, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_84 · Cited by 9 · see citing works

Multimodal Hyper-connectivity Networks for MCI Classification

Li, Y., Gao, X., Jie, B., Yap, P., Kim, M.-J., Chong-yaw Wee, A., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_50 · Cited by 9 · see citing works

Population-Shrinkage of Covariance to Estimate Better Brain Functional Connectivity

Rahim, M., Thirion, B., & Varoquaux, G. P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_53 · Cited by 8 · see citing works

Separation of Transmitted Light and Scattering Components in Transmitted Microscopy

Shimano, M., Bise, R., Zheng, Y., & Sato, I. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_2 · Cited by 8 · see citing works

Biomechanical Patient-Specific Model of the Respiratory System Based on 4D CT Scans and Controlled by Personalized Physiological Compliance

Giroux, M., Ladjal, H., Beuve, M., & Shariat, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_25 · Cited by 8 · see citing works

Anatomy-Driven Modelling of Spatial Correlation for Regularisation of Arterial Spin Labelling Images

Owen, D., Melbourne, A., Eaton-Rosen, Z., Thomas, D. L., Marlow, N., Rohrer, J. D., & Sebastien Ourselin, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_22 · Cited by 8 · see citing works

Active Learning and Proofreading for Delineation of Curvilinear Structures

Mosinska, A., Tarnawski, J., & Fua, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_19 · Cited by 7 · see citing works

UV Exposed Optical Fibers with Frequency Domain Reflectometry for Device Tracking in Intra-arterial Procedures

Parent, F., Gérard, M., Kashyap, R., & Kadoury, S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_67 · Cited by 7 · see citing works

Multi-modal EEG and fMRI Source Estimation Using Sparse Constraints

Noorzadeh, S., Maurel, P., Oberlin, T., Gribonval, R., & Barillot, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_51 · Cited by 7 · see citing works

Liver Tissue Classification in Patients with Hepatocellular Carcinoma by Fusing Structured and Rotationally Invariant Context Representation

Treilhard, J., Smolka, S., Staib, L. H., Chapiro, J., Lin, M., Shakirin, G., & Duncan, J. S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_10 · Cited by 7 · see citing works

A Mixed-Reality Approach to Radiation-Free Training of C-arm Based Surgery

Stefan, P., Habert, S., Winkler, A., Lazarovici, M., Fürmetz, J., Eck, U., & Navab, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_61 · Cited by 7 · see citing works

Supervised Discriminative EEG Brain Source Imaging with Graph Regularization

Liu, F., Hosseini, R., Rosenberger, J. M., Wang, S., & Su, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_57 · Cited by 7 · see citing works

A Multi-armed Bandit to Smartly Select a Training Set from Big Medical Data

Gutiérrez, B., Peter, L., Klein, T., & Wachinger, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_5 · Cited by 6 · see citing works

Development of a $$\upmu $$CT-based Patient-Specific Model of the Electrically Stimulated Cochlea

Çakır, A., Dawant, B. M., & Noble, J. H. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_88 · Cited by 6 · see citing works

N-way Decomposition: Towards Linking Concurrent EEG and fMRI Analysis During Natural Stimulus

Lv, J., Nguyen, V. T., van der Meer, J. N., Breakspear, M. J., & Guo, C. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_44 · Cited by 6 · see citing works

Computational Immunohistochemistry: Recipes for Standardization of Immunostaining

Arar, N. M., Pati, P., Kashyap, A., Khartchenko, A. F., Göksel, O., Kaigala, G. V., & Gabrani, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_6 · Cited by 6 · see citing works

Patient-Specific Skeletal Muscle Fiber Modeling from Structure Tensor Field of Clinical CT Images

Otake, Y., Futoshi, Y., Fukuda, N., Takao, M., Takagi, S., Yamamura, N., O’Donnell, L. J., Westin, C., Sugano, N., & Sato, Y. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_75 · Cited by 6 · see citing works

Accurate Correspondence of Cone Photoreceptor Neurons in the Human Eye Using Graph Matching Applied to Longitudinal Adaptive Optics Images

Liu, J., Jung, H., & Tam, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_18 · Cited by 6 · see citing works

Locally Affine Diffeomorphic Surface Registration for Planning of Metopic Craniosynostosis Surgery

Porras, A. R., Paniagua, B., Enquobahrie, D. A., Ensel, S., Shah, H. R., Keating, R. F., Rogers, G. F., & Linguraru, M. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_54 · Cited by 6 · see citing works

Pattern Visualization and Recognition Using Tensor Factorization for Early Differential Diagnosis of Parkinsonism

Li, R., Wu, P., Yakushev, I. Y., Wang, J., Ziegler, S. I., Förster, S., Huang, S., Schwaiger, M., Navab, N., Zuo, C., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_15 · Cited by 6 · see citing works

A Novel Automatic Segmentation Method to Quantify the Effects of Spinal Cord Injury on Human Thigh Muscles and Adipose Tissue

Mesbah, S., Shalaby, A. M., Stills, S., Soliman, A., Willhite, A. M., Harkema, S. J., Rejc, E., & El-Baz, A. S. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_79 · Cited by 6 · see citing works

Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors

Zhou, Y., Yap, P., Zhang, H., Zhang, L., Feng, Q., & Shen, D. G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_48 · Cited by 6 · see citing works

Inference and Visualization of Information Flow in the Visual Pathway Using dMRI and EEG

Deslauriers‐Gauthier, S., Lina, J., Butler, R., Bernier, P., Whittingstall, K., Rachid Deriche, B., & Descoteaux, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_58 · Cited by 6 · see citing works

Fast Estimation of Haemoglobin Concentration in Tissue Via Wavelet Decomposition

Jones, G., Clancy, N. T., Du, X., Robu, M., Arridge, S., Elson, D. S., & Stoyanov, D. V. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_12 · Cited by 5 · see citing works

Globally-Optimal Anatomical Tree Extraction from 3D Medical Images Using Pictorial Structures and Minimal Paths

Mirikharaji, Z., Zhao, M., & Hamarneh, G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_28 · Cited by 5 · see citing works

RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction

Antunes, J. T., Prasanna, P., Madabhushi, A., Tiwari, P., & Viswanath, S. E. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_53 · Cited by 5 · see citing works

Data-Driven Rank Aggregation with Application to Grand Challenges

Fishbaugh, J., Prastawa, M. W., Wang, B., Reynolds, P., Aylward, S., & Gerig, G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_85 · Cited by 5 · see citing works

Compressed Sensing on Multi-pinhole Collimator SPECT Camera for Sentinel Lymph Node Biopsy

Seppi, C., Nahum, U., von Niederhäusern, P. A., Pezold, S., Rissi, M., Haerle, S. K., & Cattin, P. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_47 · Cited by 5 · see citing works

Short Acquisition Time PET Quantification Using MRI-Based Pharmacokinetic Parameter Synthesis

Scott, C. J., Jiao, J., Cardoso, M. J., Melbourne, A., Vita, E. D., Thomas, D. L., Burgos, N., Markiewicz, P. J., Schott, J. M., Hutton, B. F., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_83 · Cited by 5 · see citing works

OptiC: Robust and Automatic Spinal Cord Localization on a Large Variety of MRI Data Using a Distance Transform Based Global Optimization

Gros, C., Leener, B. D., Dupont, S. M., Martin, A. R., Fehlings, M. G., Bakshi, R., Tummala, S., Auclair, V., McLaren, D. G., Callot, V., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_80 · Cited by 5 · see citing works

q-Space Upsampling Using x-q Space Regularization

Chen, G., Dong, B., Zhang, Y., Shen, D. G., & Yap, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_71 · Cited by 5 · see citing works

Subject-Specific Structural Parcellations Based on Randomized AB-divergences

Honnorat, N., Parker, D., Tunç, B., Davatzikos, C. A., & Verma, R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_47 · Cited by 5 · see citing works

MRI-Based Surgical Planning for Lumbar Spinal Stenosis

Abbati, G., Bauer, S., Winklhofer, S. F.-X., Schüffler, P. J., Held, U., Burgstaller, J. M., Steurer, J., & Buhmann, J. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_14 · Cited by 4 · see citing works

A Comparative Study of Breast Surface Reconstruction for Aesthetic Outcome Assessment

Lacher, R., Vasconcelos, F., Bishop, D. C., Williams, N. R., Keshtgar, M., Hawkes, D. J., Hipwell, J. H., & Stoyanov, D. V. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_58 · Cited by 4 · see citing works

Longitudinal Analysis Using Personalised 3D Cardiac Models with Population-Based Priors: Application to Paediatric Cardiomyopathies

Molléro, R., Delingette, H., Datar, M., Heimann, T., Hauser, J. A., Panesar, D., Jones, A., Taylor, A. M., Kelm, M., Kühne, T., et al. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_40 · Cited by 4 · see citing works

An Optimal Control Approach for High Intensity Focused Ultrasound Self-Scanning Treatment Planning

Möri, N., Gui, L., Jud, C., Lorton, O., Salomir, R., & Cattin, P. C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_60 · Cited by 4 · see citing works

Fast Background Removal Method for 3D Multi-channel Deep Tissue Fluorescence Imaging

Li, C., Li, X., Cao, H., Jiang, H., Deng, X., Chen, D. Z., Yang, L., & Shao, Z. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_11 · Cited by 4 · see citing works

BrainSync: An Orthogonal Transformation for Synchronization of fMRI Data Across Subjects

Joshi, A. A., Chong, M., & Leahy, R. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_56 · Cited by 4 · see citing works

Combining Spatial and Non-spatial Dictionary Learning for Automated Labeling of Intra-ventricular Hemorrhage in Neonatal Brain MRI

Liu, M., Miller, S. P., Chau, V., & Studholme, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_90 · Cited by 4 · see citing works

Multi-level Multi-task Structured Sparse Learning for Diagnosis of Schizophrenia Disease

Wang, M., Hao, X., Huang, J., Wang, K., Xu, X., & Zhang, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_6 · Cited by 4 · see citing works

Real-Time 3D Ultrasound Reconstruction and Visualization in the Context of Laparoscopy

Jayarathne, U. L., Moore, J. T., Chen, E. C. S., Pautler, S. E., & Peters, T. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_68 · Cited by 4 · see citing works

Efficient Deformable Motion Correction for 3-D Abdominal MRI Using Manifold Regression

Chen, X., Balfour, D. R., Marsden, P. K., Reader, A. J., Prieto, C., & King, A. P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_31 · Cited by 3 · see citing works

Quality Assessment of Retinal Hyperspectral Images Using SURF and Intensity Features

M’hiri, F., Chevrefils, C., & Sylvestre, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_14 · Cited by 3 · see citing works

Sparse Multi-kernel Based Multi-task Learning for Joint Prediction of Clinical Scores and Biomarker Identification in Alzheimer’s Disease

Cao, P., Liu, X., Yang, J., Zhao, D., & Zai͏̈ane, O. R. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_23 · Cited by 3 · see citing works

Field Effect Induced Organ Distension (FOrge) Features Predicting Biochemical Recurrence from Pre-treatment Prostate MRI

Ghose, S., Shiradkar, R., Rusu, M., Jhimli Mitra, A., Thawani, R., Feldman, M. D., Gupta, A. C., Purysko, A. S., Ponsky, L. E., & Madabhushi, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_50 · Cited by 3 · see citing works

Joint Representation of Connectome-Scale Structural and Functional Profiles for Identification of Consistent Cortical Landmarks in Human Brains

Zhang, S., Jiang, X., & Liu, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_46 · Cited by 3 · see citing works

Liver Lesion Detection Based on Two-Stage Saliency Model with Modified Sparse Autoencoder

Yuan, Y., Meng, M. Q. ‐., Qin, W., & Xing, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_66 · Cited by 3 · see citing works

Benchmarking Quantitative Imaging Biomarker Measurement Methods Without a Gold Standard

Madan, H., Pernuš, F., & Špiclin, Ž. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_86 · Cited by 2 · see citing works

An Unbiased Penalty for Sparse Classification with Application to Neuroimaging Data

Zhang, L., Cobzaş, D., Wilman, A. H., & Kong, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_7 · Cited by 2 · see citing works

Kernel-Regularized ICA for Computing Functional Topography from Resting-State fMRI

Wang, J., & Shi, Y. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_43 · Cited by 2 · see citing works

Selecting the Optimal Sequence for Deformable Registration of Microscopy Image Sequences Using Two-Stage MST-based Clustering Algorithm

Saha, B. N., Ray, N., McArdle, S., & Ley, K. F. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_41 · Cited by 2 · see citing works

A Bag-of-Features Approach to Predicting TMS Language Mapping Results from DSI Tractography

Khatami, M., Sakreida, K., Neuloh, G., & Schultz, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_74 · Cited by 2 · see citing works

Information Theoretic Measurement of Blood Flow Complexity in Vessels and Aneurysms: Interlacing Complexity Index

Pozo, J. M., Geers, A. J., & Frangi, A. F. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66185-8_27 · Cited by 2 · see citing works

A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI

Pisharady, P. K., Sotiropoulos, S. N., Sapiro, G., & Lenglet, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_69 · Cited by 2 · see citing works

Nonlinear Feature Space Transformation to Improve the Prediction of MCI to AD Conversion

Zhang, P., Shi, B., Smith, C. D., & Liu, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_2 · Cited by 2 · see citing works

Manifold Learning of COPD

Bragman, F., McClelland, J. R., Jacob, J., Hurst, J. R., & Hawkes, D. J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_67 · Cited by 2 · see citing works

Modeling Cognitive Trends in Preclinical Alzheimer’s Disease (AD) via Distributions over Permutations

Plumb, G., Clark, L. R., Johnson, S. C., & Singh, V. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66179-7_78 · Cited by 1 · see citing works

TBS: Tensor-Based Supervoxels for Unfolding the Heart

Oda, H., Roth, H. R., Bhatia, K. K., Oda, M., Kitasaka, T., Akita, T., Schnabel, J. A., & Mori, K. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_78 · Cited by 1 · see citing works

Denoising Moving Heart Wall Fibers Using Cartan Frames

Samari, B., Aumentado‐Armstrong, T., Strijkers, G. J., Froeling, M., & Kaleem Siddiqi, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_77 · Cited by 1 · see citing works

Multi-way Regression Reveals Backbone of Macaque Structural Brain Connectivity in Longitudinal Datasets

Zhang, T., Xiao, L., Zhao, L., Hu, X., Liu, T., & Guo, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66182-7_49 · Cited by 1 · see citing works

Error estimation of deformable image registration of pulmonary CT scans using convolutional neural networks

Eppenhof, K. A. J., & Pluim, J. P. W. (2018) · Journal of medical imaging · doi:10.1117/1.jmi.5.2.024003 · Cited by 58 · see citing works

Applications of Neural Networks in Biomedical Data Analysis

Weiss, R., Karimijafarbigloo, S., Roggenbuck, D., & Rödiger, S. (2022) · Biomedicines · doi:10.3390/biomedicines10071469 · Cited by 43 · see citing works

Imaging functional neuroplasticity in human white matter tracts

Frizzell, T. O., Phull, E., Khan, M., Song, X., Grajauskas, L. A., Gawryluk, J. R., & D’Arcy, R. C. N. (2021) · Brain Structure and Function · doi:10.1007/s00429-021-02407-4 · Cited by 40 · see citing works

Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank

Tarroni, G., Bai, W., Oktay, O., Schuh, A., Suzuki, H., Glocker, B., Matthews, P. M., & Rueckert, D. (2020) · Scientific Reports · doi:10.1038/s41598-020-58212-2 · Cited by 34 · see citing works

Topological principles and developmental algorithms might refine diffusion tractography

Innocenti, G. M., Dyrby, T. B., Girard, G., St‐Onge, E., Thiran, J., Daducci, A., & Descoteaux, M. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1759-1 · Cited by 20 · see citing works

Toward quantitative three-dimensional microvascular networks segmentation with multiview light-sheet fluorescence microscopy

Kennel, P., Colombelli, J., Teyssedre, L., & Plouraboué, F. (2018) · Journal of Biomedical Optics · doi:10.1117/1.jbo.23.8.086002 · Cited by 18 · see citing works

Minimally interactive placenta segmentation from three-dimensional ultrasound images

Oguz, I., Yushkevich, N., Pouch, A. M., Oguz, B. U., Wang, J., Parameshwaran, S., Gee, J. C., Yushkevich, P. A., & Schwartz, N. (2020) · Journal of Medical Imaging · doi:10.1117/1.jmi.7.1.014004 · Cited by 13 · see citing works

Large Language Models in Cancer Imaging: Applications and Future Perspectives

Tordjman, M., Bolger, I., Yuce, M., Restrepo, F., Liu, Z., Dercle, L., McGale, J., Meribout, A., Liu, M., Beddok, A., et al. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14103285 · Cited by 12 · see citing works

Leveraging anatomical priors for automated pancreas segmentation on abdominal CT

Prasad, A. V., Mathai, T. S., Mukherjee, P., Liu, J., & Summers, R. M. (2025) · SPIE Medical Imaging: Computer-Aided Diagnosis · doi:10.1117/12.3048976 · Cited by 6 · see citing works

Deep Reinforcement Learning for Detection of Abnormal Anatomies

Diez, P. L., Juhl, K. A., Sundgaard, J. V., Diab, H., Margeta, J., Patou, F., & Paulsen, R. R. (2022) · Proceedings of the Northern Lights Deep Learning Workshop · doi:10.7557/18.6280 · Cited by 6 · see citing works

A coarse-to-fine registration method for three-dimensional MR images

Li, C.-X., Zhou, Y., Li, Y., & Yang, S. (2021) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-021-02317-x · Cited by 5 · see citing works

Diagnostic performance and confidence of an optimized deep-learning algorithm for the detection of intracranial hemorrhages

Tombach, F., Krompaß, K., Hennes, J.-L., Weber, A., Grunz, J., Huflage, H., Bley, T. A., Heidenreich, J. F., & Gruschwitz, P. (2026) · Insights into Imaging · doi:10.1186/s13244-026-02249-w · Cited by 2 · see citing works

Patient-specific electro-anatomical modeling of cochlear implants using deep neural networks

Liu, Z., & Noble, J. H. (2022) · SPIE Medical Imaging: Image-Guided Procedures, Robotic Interventions, and Modeling · doi:10.1117/12.2611596 · Cited by 2 · see citing works

Estimation of axonal conduction speed and the inter hemispheric transfer time using connectivity informed maximum entropy on the mean

Deslauriers‐Gauthier, S., & Rachid Deriche, B. (2019) · SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging · doi:10.1117/12.2511736 · Cited by 2 · see citing works

How to Register a Live onto a Liver ? Partial Matching in the Space of Varifolds

Antonsanti, P.-L., Benseghir, T., Jugnon, V., Ghosn, M., Chassat, P., Glaunès, J., & Kaltenmark, I. (2022) · The Journal of Machine Learning for Biomedical Imaging · doi:10.59275/j.melba.2022-f8ba · Cited by 2 · see citing works

VolPAM: Volumetric Phenotype-Activation-Map for data-driven discovery of 3D imaging phenotypes and interpretability

Norouzi, M., Khan, S. S., & Ashraf, A. B. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-09172-x · Cited by 1 · see citing works

COVID 19: Data Augmentation and Image Preprocessing Technique

Ishwarya, K., Varun, C. S., Saraswathi, S., & Devi, D. M. R. (2023) · International Conference on Recent Trends in Advance Computing (ICRTAC) · doi:10.1109/icrtac59277.2023.10480797 · Cited by 1 · see citing works

Algorithm Selection in Multimodal Medical Image Registration

Elkeshreu, H., & Basir, O. (2020) · IRA-International Journal of Applied Sciences · doi:10.21013/jas.v14.n2.p1

Semantic Segmentation of 3D Medical Images with 3D Convolutional Neural Networks

Herrera, A. M., Cuadros-Vargas, A. J., & Pedrini, H. (2020) · CLEI electronic journal · doi:10.19153/cleiej.23.1.4

Advances in Deep Learning for Video Anomaly Detection: A Comprehensive Review

Gupta, R., & Tyagi, N. (2025) · International Conference on Emerging Trends in Engineering and Technology (ICETET) · doi:10.1109/icetetsip64213.2025.11156929

A 3D neural network with adaptive loss and residual connections for intracochlear potential mapping and electro-anatomical model optimization

Vu, M. Q. H., Bratu, E. L., & Noble, J. H. (2026) · SPIE Medical Imaging: Image-Guided Procedures, Robotic Interventions, and Modeling · doi:10.1117/12.3087915

Automated quantification of coronal balance in spinal deformity: a safety-aware clinical workflow

Wang, Z., Zhang, Y., Xue, F., Maimaiti, A., Li, Y., Zhang, J., Zhao, W., & Yang, Y. (2026) · Scientific Reports · doi:10.1038/s41598-026-47402-z

Fluoroscopy-Guided Motion Management in Particle Therapy: Evolution, Challenges, and AI-Enabled Opportunities

Li, F., Furutani, K. M., & Beltran, C. J. (2026) · Tomography · doi:10.3390/tomography12050066

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014

Golland, P., 波多伸彦, Barillot, C., Joachim Hornegger, A., & Howe, R. D. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10404-1 · Cited by 24 · see citing works

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015

Navab, N., Joachim Hornegger, A., Wells, W. M., & Frangi, A. F. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4 · Cited by 545 · see citing works

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013

Mori, K., Sakuma, I., Sato, Y., Barillot, C., & Navab, N. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40811-3 · Cited by 10 · see citing works

Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

Martel, A. L., Abolmaesumi, P., Stoyanov, D. V., Mateus, D., Zuluaga, M. A., Zhou, S., Racoceanu, D., & Leo Joskowicz, B. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59725-2 · Cited by 129 · see citing works

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011

Gabor Fichtinger, A., Peters, T., & Martel, A. L. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-23629-7 · Cited by 5 · see citing works