Deep Learning in Multimodal Medical Image Analysis

A survey on deep learning in medical image analysis

Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.07.005 · Cited by 15,332 · see citing works

An overview of deep learning in medical imaging focusing on MRI

Lundervold, A. S., & Lundervold, A. (2018) · NORA - Norwegian Open Research Archives · Cited by 1,012 · see citing works

Medical image fusion: A survey of the state of the art

James, A. P., & Dasarathy, B. V. (2014) · Information Fusion · doi:10.1016/j.inffus.2013.12.002 · Cited by 977 · see citing works

Hierarchical Feature Representation and Multimodal Fusion with Deep Learning for AD/MCI Diagnosis

Suk, H.-I., Lee, S.-W., & Shen, D. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.077 · Cited by 968 · see citing works

Deep convolutional neural networks for multi-modality isointense infant brain image segmentation

Zhang, W., Li, R., Deng, H., Wang, L., Lin, W., Ji, S., & Shen, D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.061 · Cited by 817 · see citing works

Deep Learning in Medical Ultrasound Analysis: A Review

Liu, S., Wang, Y., Yang, X., Lei, B., Liu, L., Li, S. X., Ni, D., & Wang, T. (2019) · Engineering · doi:10.1016/j.eng.2018.11.020 · Cited by 798 · see citing works

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

Deep MR to CT Synthesis Using Unpaired Data

Wolterink, J. M., Dinkla, A. M., Savenije, M. H. F., Seevinck, P. R., van den Berg, C. A. T., & Išgum, I. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-68127-6_2 · Cited by 652 · see citing works

Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease

Liu, S., Liu, S., Cai, W., Che, H., Pujol, S., Kikinis, R., Feng, D., Fulham, M. J., & ADNI (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2372011 · Cited by 637 · see citing works

Deep Learning-Based Feature Representation for AD/MCI Classification

Suk, H., & Shen, D. G. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40763-5_72 · Cited by 463 · see citing works

Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network

Zhang, Z., Yang, L., & Zheng, Y. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00963 · Cited by 455 · see citing works

Deep Learning-Based Image Segmentation on Multimodal Medical Imaging

Guo, Z., Li, X., Huang, H., Guo, N., & Li, Q. (2019) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2018.2890359 · Cited by 445 · see citing works

Multimodal neuroimaging feature learning with multimodal stacked deep polynomial networks for diagnosis of Alzheimer’s disease

Shi, J., Zheng, X., Li, Y., Zhang, Q., & Ying, S. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2655720 · Cited by 444 · see citing works

Fully convolutional networks for multi-modality isointense infant brain image segmentation

Nie, D., Wang, L., Gao, Y., & Shen, D. (2016) · 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2016.7493515 · Cited by 304 · see citing works

A Robust Deep Model for Improved Classification of AD/MCI Patients

Li, F., Tran, L., Thung, K., Ji, S., Shen, D. G., & Jiang, L. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2429556 · Cited by 300 · see citing works

3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients

Nie, D., Zhang, H., Adeli, E., Liu, L., & Shen, D. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46723-8_25 · Cited by 282 · see citing works

SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

Huo, Y., Xu, Z., Moon, H., Bao, S., Assad, A., Moyo, T. K., Savona, M. R., Abramson, R. G., & Landman, B. A. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2876633 · Cited by 278 · see citing works

Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models

Carneiro, G., Nascimento, J. C., & Bradley, A. P. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_78 · Cited by 252 · see citing works

Adversarial Image Synthesis for Unpaired Multi-modal Cardiac Data

Chartsias, A., Joyce, T., Dharmakumar, R., & Tsaftaris, S. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-68127-6_1 · Cited by 194 · see citing works

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image

Xiang, L., Wang, Q., Nie, D., Zhang, L., Jin, X., Qiao, Y., & Shen, D. G. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.03.011 · Cited by 183 · see citing works

Natural Image Bases to Represent Neuroimaging Data

Gupta, A., Ayhan, M. S., & Maida, A. S. (2013) · Cited by 170 · see citing works

Cross-Domain Synthesis of Medical Images Using Efficient Location-Sensitive Deep Network

Nguyen, H. V., Zhou, K., & Vemulapalli, R. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24553-9_83 · Cited by 130 · see citing works

Towards Adversarial Retinal Image SynthesisPreprint

Costa, P., Galdrán, A., Meyer, M. I., Abràmoff, M. D., Niemeijer, M., Mendonça, A. M., & Campilho, A. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.08974 · Cited by 101 · see citing works

Nonlinear feature transformation and deep fusion for Alzheimer's Disease staging analysis

Shi, B., Chen, Y., Zhang, P., Smith, C. D., & Liu, J. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.09.032 · Cited by 92 · see citing works

Whole Image Synthesis Using a Deep Encoder-Decoder Network

Sevetlidis, V., Giuffrida, M. V., & Tsaftaris, S. A. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46630-9_13 · Cited by 68 · see citing works

Classification of breast lesions using cross-modal deep learning

Hadad, O., Bakalo, R., Ben‐Ari, R., Hashoul, S., & Amit, G. (2017) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2017.7950480 · Cited by 66 · see citing works

Multi-stream 3D FCN with multi-scale deep supervision for multi-modality isointense infant brain MR image segmentation

Zeng, G., & Guoyan Zheng, A. (2018) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2018.8363540 · Cited by 42 · see citing works

A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets

Bayoudh, K., Knani, R., Hamdaoui, F., & Mtibaa, A. (2022) · The Visual Computer · doi:10.1007/s00371-021-02166-7 · Cited by 456 · see citing works

A systematic review of intermediate fusion in multimodal deep learning for biomedical applications

Guarrasi, V., Aksu, F., Caruso, C. M., Di Feola, F., Rofena, A., Ruffini, F., & Soda, P. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105509 · Cited by 95 · see citing works

Multimodality, inclusive design and intuitive use

(2009) · Cited by 8 · see citing works

Factors Influencing Modality Choice in Multimodal Applications

Naumann, A. B., Wechsung, I., & Möller, S. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-69369-7_5 · Cited by 15 · see citing works

Multimodal and Federated Interaction

(2008) · doi:10.4018/978-1-59904-832-1.ch021 · Cited by 3 · see citing works

Study of communication modalities for teaching distance information

Fastelli, F., Simon, C., Ricca, A., & Chellali, A. (2022) · IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) · doi:10.1109/vrw55335.2022.00204

Multimodal and Federated Interaction

(2009) · doi:10.4018/978-1-87828-991-9.ch009 · Cited by 2 · see citing works