Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks

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Deep-Learning Aided Atomic-Scale Phase Segmentation toward Diagnosing Complex Oxide Cathodes for Lithium-Ion Batteries

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Blind Identification of LDPC Code Based on Deep Learning

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Innovative deep learning architectures for medical image diagnosis: a comprehensive review of convolutional, recurrent, and transformer models

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Magnetic resonance imaging manifestations of cerebral small vessel disease: automated quantification and clinical application

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U-NetCTS: U-Net deep neural network for fully automatic segmentation of 3D CT DICOM volume

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Automatic segmentation of the spinal cord nerve rootlets

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PointCHD: A Point Cloud Benchmark for Congenital Heart Disease Classification and Segmentation

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Automatic segmentation of colorectal cancer in 3D MRI by combining deep learning and 3D level-set algorithm-a preliminary study

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Multiclass Brain Tissue Segmentation in 4D CT Using Convolutional Neural Networks

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Multi stream 3D hyper-densely connected network for multi modality isointense infant brain MRI segmentation

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Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem

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Fat-saturated image generation from multi-contrast MRIs using generative adversarial networks with Bloch equation-based autoencoder regularization

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Machine learning predictions for lost time injuries in power transmission and distribution projects

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Automatic Prostate Gleason Grading Using Pyramid Semantic Parsing Network in Digital Histopathology

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Attention-guided deep neural network with a multichannel architecture for lung nodule classification

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SDResU-Net: Separable and Dilated Residual U-Net for MRI Brain Tumor Segmentation

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Modeling Brain Diverse and Complex Hemodynamic Response Patterns via Deep Recurrent Autoencoder

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Discriminating between benign and malignant breast tumors using 3D convolutional neural network in dynamic contrast enhanced-MR images

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CMB-HUNT: Automatic detection of cerebral microbleeds using a deep neural network

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Significant Dimension Reduction of 3D Brain MRI using 3D Convolutional Autoencoders

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3D-VNPU: A Flexible Accelerator for 2D/3D CNNs on FPGA

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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System

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Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network

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CT-Based Quantitative Analysis for Pathological Features Associated With Postoperative Recurrence and Potential Application Upon Artificial Intelligence: A Narrative Review With a Focus on Chronic Subdural Hematomas

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Automated Multimodal Fusion Technique for the Classification of Human Brain on Alzheimer’s Disorder

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Automated detection of cerebral microbleeds on MR images using knowledge distillation framework

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Machine and deep learning algorithms for classifying different types of dementia: A literature review

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Automatic detection of brachytherapy seeds in 3D ultrasound images using a convolutional neural network

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StainCNNs: An efficient stain feature learning method

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Exploration of Memory Access Optimization for FPGA-based 3D CNN Accelerator

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Automatic Tumor Segmentation by Means of Deep Convolutional U-Net With Pre-Trained Encoder in PET Images

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Artificial Intelligence and Stroke Imaging

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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI

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Synthetic microbleeds generation for classifier training without ground truth

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Computer-aided extraction of select MRI markers of cerebral small vessel disease: A systematic review

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A Comprehensive Analysis of Early Alzheimer Disease Detection from 3D sMRI Images Using Deep Learning Frameworks

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Brain age prediction of healthy subjects on anatomic MRI with deep learning: going beyond with an "explainable AI" mindsetPreprint

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Electrochemical Biosensing and Deep Learning-Based Approaches in the Diagnosis of COVID-19: A Review

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Cerebral Microbleed Detection Via Fourier Descriptor with Dual Domain Distribution Modeling

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Deep Learning for Medical Image Recognition: Open Issues and a Way to Forward

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Application of Convolutional Dendrite Net for Detection of Myocardial Infarction Using ECG Signals

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Generalization of intensity distribution of medical images using GANs

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Hybrid CNN-transformer network for interactive learning of challenging musculoskeletal images

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Automating vessel segmentation in the heart and brain: A trend to develop multi-modality and label-efficient deep learning techniques

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Mobile Phone based ensemble classification of Deep Learned Feature for Medical Image Analysis

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One stage lesion detection based on 3D context convolutional neural networks

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Deep learning kidney segmentation with very limited training data using a cascaded convolution neural network

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Automatic localization of anatomical landmarks in cardiac MR perfusion using random forests

Kim, Y., Chung, Y., & Choe, Y. H. (2017) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2017.07.001 · Cited by 13

2D and 3D Convolutional Neural Network Fusion for Predicting the Histological Grade of Hepatocellular Carcinoma

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A Novel Radiogenomics Framework for Genomic and Image Feature Correlation using Deep Learning

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Automatic Detection of Tumor Buds in Pan-Cytokeratin Stained Colorectal Cancer Sections by a Hybrid Image Analysis Approach

Bergler, M., Benz, M., Rauber, D., Hartmann, D., Kötter, M., Eckstein, M., Schneider‐Stock, R., Hartmann, A., Merkel, S., Bruns, V., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-23937-4_10 · Cited by 13

A Multimodality-Contribution-Aware TripNet for Histologic Grading of Hepatocellular Carcinoma

Jia, X., Sun, Z., Mi, Q., Yang, Z., & Yang, D. (2021) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2021.3079216 · Cited by 13

Automatic Interpretation of Carotid Intima–Media Thickness Videos Using Convolutional Neural Networks

Tajbakhsh, N., Shin, J. Y., Hurst, R. T., Kendall, C. B., & Liang, J. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-810408-8.00007-9 · Cited by 14

Artificial Intelligence-Powered Mammography: Navigating the Landscape of Deep Learning for Breast Cancer Detection

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Involving logical clinical knowledge into deep neural networks to improve bladder tumor segmentation

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Is diffuse axonal injury on susceptibility weighted imaging a biomarker for executive functioning in adolescents with traumatic brain injury?

Linden, C. V., Verhelst, H., Genbrugge, E., Deschepper, E., Caeyenberghs, K., Vingerhoets, G., & Deblaere, K. (2019) · European Journal of Paediatric Neurology · doi:10.1016/j.ejpn.2019.04.003 · Cited by 12

Calculating the target exposure index using a deep convolutional neural network and a rule base

Takaki, T., Murakami, S., Watanabe, R., Aoki, T., & Fujibuchi, T. (2020) · Physica Medica · doi:10.1016/j.ejmp.2020.02.012 · Cited by 14

Application of Deep Learning in Biomedical Informatics and Healthcare

Nayak, D. K., Mishra, P., Das, P., Jamader, A. R., & Acharya, B. (2021) · Intelligent systems reference library · doi:10.1007/978-981-16-5304-9_9 · Cited by 13

Detection of Cerebral Microbleeds in MR Images Using a Single‐Stage Triplanar Ensemble Detection Network (TPE‐Det)

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“How much realism is needed?” — the wrong question in silico imagers have been asking

Badano, A. G. (2017) · Medical Physics · doi:10.1002/mp.12187 · Cited by 12

A Systematic Approach for Deep Learning Based Brain Tumor Segmentation

Sille, R., Choudhury, T., Chauhan, P., & Sharma, D. (2021) · Ingénierie des systèmes d information · doi:10.18280/isi.260301 · Cited by 12

Cerebral Microbleed Automatic Detection System Based on the “Deep Learning”

Fan, P., Shan, W., Yang, H., Zheng, Y., Wu, Z., Chan, S. W., Wang, Q., Gao, P., Liu, Y., He, K., et al. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.807443 · Cited by 12

A CADe System for Gliomas in Brain MRI using Convolutional Neural NetworksPreprint

Banerjee, S., Mitra, S., Sharma, A. K., & Shankar, B. U. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.07589 · Cited by 15

A Survey on Biomedical Image CaptioningPreprint

Kougia, V., Pavlopoulos, J., & Androutsopoulos, I. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.13302 · Cited by 12

Unsupervised Medical Image Segmentation with Adversarial Networks: From Edge Diagrams to Segmentation MapsPreprint

Sivanesan, U., Braga, L. H., Sonnadara, R., & Dhindsa, K. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.05140 · Cited by 20

A deep learning pipeline for systematic and accurate vertebral fracture reporting in computed tomography

Glessgen, C., Cyriac, J., Yang, S., Manneck, S., Wichtmann, H. M., Fischer, A. M., Breit, H., & Harder, D. (2025) · Clinical Radiology · doi:10.1016/j.crad.2025.106827 · Cited by 11

Cloud Driven Framework for Skin Cancer Detection using Deep CNN

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Diffusion-weighted imaging-based radiomics for predicting 1-year ischemic stroke recurrence

Wang, H., Sun, Y., Zhu, J., Zhuang, Y., & Song, B. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.1012896 · Cited by 11

Deep learning-based quantitative analysis of dental caries using optical coherence tomography: an ex vivo study

Salehi, H. S., Mahdian, M., Murshid, M. M., Judex, S., & Tadinada, A. (2019) · Lasers in Dentistry · doi:10.1117/12.2510076 · Cited by 13

A Novel Point Cloud Encoding Method Based on Local Information for 3D Classification and Segmentation

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A spatiotemporal correlation deep learning network for brain penumbra disease

Liu, L., Zhang, P., Liang, G., Xiong, S., Wang, J., & Zheng, G. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.11.041 · Cited by 11

Deep-learning strategy for pulmonary artery-vein classification of non-contrast CT images

Nardelli, P., Jiménez‐Carretero, D., Bermejo-Peláez, D., Ledesma‐Carbayo, M. J., Rahaghi, F. N., & Estépar, R. S. J. (2017) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2017.7950543 · Cited by 12

Reconstruction of undersampled radial free‐breathing 3D abdominal MRI using stacked convolutional auto‐encoders

Lv, J., Chen, K., Yang, M. Y., Zhang, J., & Wang, X. (2018) · Medical Physics · doi:10.1002/mp.12870 · Cited by 12

An Introduction to Deep Learning Applications In MRI Images

Datta, P., & Rohilla, R. (2019) · International Conference on Power Energy, Environment and Intelligent Control (PEEIC) · doi:10.1109/peeic47157.2019.8976727 · Cited by 11

Keratoconus Detection Algorithm using Convolutional Neural Networks: Challenges

Lavric, A., Popa, V., David, C., & Paval, C. C. (2019) · International Conference on Electronics, Computers and Artificial Intelligence (ECAI) · doi:10.1109/ecai46879.2019.9042100 · Cited by 11

Virtual digital subtraction angiography using multizone patch-based U-Net

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Segmentation and Approximation of Blood Volume in Intracranial Hemorrhage Patients Based on Computed Tomography Scan Images Using Deep Learning Method

Irene, K., Ma’Sum, M. A., Yunus, R. E., & Jatmiko, W. (2020) · International Workshop on Big Data and Information Security (IWBIS) · doi:10.1109/iwbis50925.2020.9255593 · Cited by 11

3D Multi-Scale Residual Network Toward Lacunar Infarcts Identification From MR Images With Minimal User Intervention

Al‐masni, M. A., Kim, W., Kim, E. Y., Noh, Y., & Kim, D. (2021) · IEEE Access · doi:10.1109/access.2021.3051274 · Cited by 11

Classification of Brain Tumor using PCA-RF in MR Neurological Images

Saraswathi, V., & Gupta, D. (2019) · International Conference on Communication Systems & Networks (COMSNETS) · doi:10.1109/comsnets.2019.8711010 · Cited by 11

Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network ApproachPreprint

Lahiri, A., Jain, V., Mondal, A. K., & Biswas, P. K. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.01348 · Cited by 11

Design and Implementation of CNN for detecting Melanoma through Image Processing

Ranjan, S. (2018) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2018.3522 · Cited by 10

Naïve Bayes classifier assisted automated detection of cerebral microbleeds in susceptibility-weighted imaging brain images

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Toward automated detection of microbleeds with anatomical scale localization using deep learning

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3D Cnn-Based Soma Segmentation from Brain Images at Single-Neuron Resolution

Meng, D., Liu, D., Xiong, Z., Yang, C., Chen, X., Zha, Z.-J., Bi, G., & Wu, F. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451389 · Cited by 10

Reinventing 2D Convolutions for 3D Medical Images

Yang, J., Huang, X., Ni, B., Xu, J., Yang, C., & Xu, G. (2019) · Cited by 10

Image‐based deep learning reveals the responses of human motor neurons to stress and VCP ‐related ALS

Verzat, C., Harley, J., Patani, R., & Luisier, R. (2021) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12770 · Cited by 10

Skin Lesions Detection and Classification Using Deep Learning

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