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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Deep Learning Papers on Medical Image Analysis
| Date | Stars |
|---|---|
| 2026-07-31 | 1611 |
| 2026-08-05 | 1611 |
| 2026-08-06 | 1611 |
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# Deep Learning Papers on Medical Image Analysis ## Background To the best of our knowledge, this is the first list of deep learning papers on medical applications. There are couple of lists for deep learning papers in general, or computer vision, for example [Awesome Deep Learning Papers](https://github.com/terryum/awesome-deep-learning-papers.git). In this list, I try to classify the papers based on their deep learning techniques and learning methodology. I believe this list could be a good starting point for DL researchers on Medical Applications. ## Criteria 1. A list of **top deep learning papers** published since 2015. 2. Papers are collected from peer-reviewed journals and high reputed conferences. However, it may have recent papers on arXiv. 3. A meta-data is required along with the paper, i.e. Deep Learning technique, Imaging Modality, Area of Interest, Clinical Database (DB). *List of Journals / Conferences (J/C):* - **[Medical Image Analysis (MedIA)](https://www.journals.elsevier.com/medical-image-analysis/)** - **[IEEE Transaction on Medical Imaging (IEEE-TMI)](https://ieee-tmi.org/)** - **[IEEE Transaction on Biomedical Engineering (IEEE-TBME)](http://tbme.embs.org/)** - **[IEEE Journal of Biomedical and Health Informatics (IEEE-JBHI)](http://jbhi.embs.org/)** - **[International Journal on Computer Assisted Radiology and Surgery (IJCARS)](http://www.springer.com/medicine/radiology/journal/11548)** - **International Conference on Information Processing in Medical Imaging (IPMI)** - **International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)** - **International Conference on Information Processing in Computer-Assisted Interventions (IPCAI)** - **IEEE International Symposium on Biomedical Imaging (ISBI)** ## Shortcuts *Deep Learning Techniques:* - NN: Neural Networks - MLP: Multilayer Perceptron - RBM: Restricted Boltzmann Machine - SAE: Stacked Auto-Encoders - CAE: Convolutional Auto-Encoders - CNN: Convolutional Neural Networks - RNN: Recurrent Neural Networks - LSTM: Long Short Term Memory - M-CNN: Multi-Scale/View/Stream CNN - MIL-CNN: Multi-instance Learning CNN - FCN: Fully Convolutional Networks *Imaging Modality:* - US: Ultrasound - MR/MRI: Magnetic Resonance Imaging - PET: Positron Emission Tomography - MG: Mammography - CT: Computed Tompgraphy - H&E: Hematoxylin & Eosin Histology Images - RGB: Optical Images ## Table of Contents ### Deep Learning Techniques * [AutoEncoders/ Stacked AutoEncoders](#autoencoders--stacked-autoencoders) * [Convolutional Neural Networks](#convolutional-neural-networks) * [Recurrent Neural Networks](#recurrent-neural-networks) * [Generative Adversarial Networks](#generative-adversarial-networks) ### Medical Applications * [Annotation](#annotation) * [Classification](#classification) * [Detection/ Localization](#detection--localization) * [Segmentation](#segmentation) * [Registration](#registration) * [Regression](#regression) * [Image Reconstruction and Post-Processing](#https://arxiv.org/abs/1707.05927) * [Other tasks](#other-tasks) * * * ### Deep Learning Techniques #### Auto-Encoders/ Stacked Auto-Encoders - #### Convolutional Neural Networks - [AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images](http://ieeexplore.ieee.org/document/7405343/) - [Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images](http://ieeexplore.ieee.org/document/7401052/#full-text-section) #### Recurrent Neural Networks - #### Generative Adversarial Networks - [Adversarial Deep Structured Nets for Mass Segmentation from Mammograms](https://arxiv.org/abs/1710.09288) ### Medical Applications #### Annotation | Technique | Modality | Area | Paper Title| DB | J/C | Year | | ------ | ----------- | ----------- | ----------- |---|----------- | ---- | | NN | H&E | N/A | Deep learning of feature representation with multiple ins
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Alex Bailo · Netherlands
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ac46f9216b2ab94f, llm:Repository is an 'awesome' curated list of deep learning papers for medical image analysis (README: 'Deep Learning Papers on Medical Image Analysis', topics: awesome-list, deep-learning, medical-imaging, medical-informatics).