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Deep Learning Papers on Medical Image Analysis

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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. 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):

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

Medical Applications

Deep Learning Techniques

Auto-Encoders/ Stacked Auto-Encoders

Convolutional Neural Networks

Recurrent Neural Networks

Generative Adversarial Networks

Medical Applications

Annotation

Technique Modality Area Paper Title DB J/C Year
NN H&E N/A Deep learning of feature representation with multiple instance learning for medical image analysis [pdf] ICASSP 2014
M-CNN H&E Breast AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images [pdf] AMIDA IEEE-TMI 2016
FCN H&E N/A Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation pdf MICCAI 2017

Classification

Technique Modality Area Paper Title DB J/C Year
M-CNN CT Lung Multi-scale Convolutional Neural Networks for Lung Nodule Classification [pdf] LIDC-IDRI IPMI 2015
3D-CNN MRI Brain Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks [pdf] ADNI arXiv 2015
CNN+RNN RGB Eye Automatic Feature Learning to Grade Nuclear Cataracts Based on Deep Learning [pdf] IEEE-TBME 2015
CNN X-ray Knee Quantifying Radiographic Knee Osteoarthritis Severity using Deep Convolutional Neural Networks [pdf] O.E.1 arXiv 2016
CNN H&E Thyroid A Deep Semantic Mobile Application for Thyroid Cytopathology [pdf] SPIE 2016
3D-CNN, 3D-CAE MRI Brain Alzheimer's Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network [pdf] ADNI arXiv 2016
M-CNN RGB Skin Multi-resolution-tract CNN with hybrid pretrained and skin-lesion trained layers [pdf] Dermofit MLMI 2016
CNN RGB Skin, Eye Towards Automated Melanoma Screening: Exploring Transfer Learning Schemes [pdf] EDRA, DRD arXiv 2016
M-CNN CT Lung Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks [pdf] LIDC-IDRI, ANODE09, DLCST IEEE-TMI 2016
3D-CNN CT Lung DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification [pdf] LIDC-IDRI, LUNA16 IEEE-WACV 2018
3D-CNN MRI Brain 3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients [pdf] MICCAI 2016
SAE US, CT Breast, Lung Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans [pdf] LIDC-IDRI Nature 2016
CAE MG Breast Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring [pdf] IEEE-TMI 2016
MIL-CNN MG Breast Deep multi-instance networks with sparse label assignment for whole mammogram classification [pdf] INbreast MICCAI 2017
GCN MRI Brain Spectral Graph Convolutions for Population-based Disease Prediction [pdf] ADNI, ABIDE arXiv 2017
CNN RGB Skin Dermatologist-level classification of skin cancer with deep neural networks Nature 2017
FCN + CNN MRI Liver-Liver Tumor SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks [pdf] ISBI 2017

Detection / Localization

Technique Modality Area Paper Title DB J/C Year
MLP CT Head-Neck 3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data [pdf] MICCAI 2015
CNN US Fetal Standard Plane Localization in Fetal Ultrasound via Domain Transferred Deep Neural Networks [pdf] IEEE-JBHI 2015
2.5D-CNN MRI Femur Automated anatomical landmark detection ondistal femur surface using convolutional neural network [pdf] OAI ISBI 2015
LSTM US Fetal Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks [pdf] MICCAI 2015
CNN X-ray, MRI Hand Regressing Heatmaps for Multiple Landmark Localization using CNNs [pdf] DHADS MICCAI 2016
CNN MRI, US, CT - An artificial agent for anatomical landmark detection in medical images [pdf] SATCOM MICCAI 2016
FCN US Fetal Real-time Standard Scan Plane Detection and Localisation in Fetal Ultrasound using Fully Convolutional Neural Networks [pdf] MICCAI 2016
CNN+LSTM MRI Heart Recognizing end-diastole and end-systole frames via deep temporal regression network [pdf] MICCAI 2016
M-CNN MRI Heart Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation Neural Networks [pdf] IEEE-TMI 2016
CNN PET/CT Heart Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique Neural Networks [pdf] MP 2016
3D-CNN MRI Brain Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks [pdf] IEEE-TMI 2016
CNN X-ray, MG - Self-Transfer Learning for Fully Weakly Supervised Lesion Localization [pdf] NIH,China, DDSM,MIAS MICCAI 2016
CNN RGB Eye Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images [pdf] DRD, MESSIDOR MICCAI 2016
GAN - - Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery IPMI 2017
FCN X-ray Cardiac CathNets: Detection and Single-View Depth Prediction of Catheter Electrodes MIAR 2016
3D-CNN CT Lung DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification [pdf] LIDC-IDRI, LUNA16 IEEE-WACV 2018
3D-CNN CT Lung DeepEM: Deep 3D ConvNets with EM for weakly supervised pulmonary nodule detection [pdf] LIDC-IDRI, LUNA16 MICCAI 2018

Segmentation

Technique Modality Area Paper Title DB J/C Year
U-Net - - U-net: Convolutional networks for biomedical image segmentation MICCAI 2015
FCN MRI Head-Neck Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation [pdf] arXiv 2016
U-Net CT Head-Neck AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy [pdf] Medical Physics 2018
FCN CT Liver-Liver Tumor Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields [pdf] MICCAI 2016
3D-CNN MRI Spine Model-Based Segmentation of Vertebral Bodies from MR Images with 3D CNNs MICCAI 2016
FCN CT Liver-Liver Tumor Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks [pdf] arXiv 2017
FCN MRI Liver-Liver Tumor SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks [pdf] ISBI 2017
3D-CNN Diffusion MRI Brain q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI [pdf] (Section II.B.2) IEEE-TMI 2016
GAN MG Breast Mass Adversarial Deep Structured Nets for Mass Segmentation from Mammograms [pdf] INbreast, DDSM-BCRP ISBI 2018
3D-CNN CT Liver 3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes pdf MICCAI 2017
3D-CNN MRI Brain Unsupervised domain adaptation in brain lesion segmentation with adversarial networks pdf IPMI 2017
FCN FUNDUS Retina A Fully Convolutional Neural Network based Structured Prediction Approach Towards the Retinal Vessel Segmentation pdf ISBI 2017

Registration

Technique Modality Area Paper Title DB J/C Year
3D-CNN CT Spine An Artificial Agent for Robust Image Registration [pdf] 2016

Regression

Technique Modality Area Paper Title DB J/C Year
2.5D-CNN MRI Automated anatomical landmark detection ondistal femur surface using convolutional neural network [pdf] OAI ISBI 2015
3D-CNN Diffusion MRI Brain q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI [pdf] (Section II.B.1) [HCP] and other IEEE-TMI 2016

Image Reconstruction and Post Processing

Technique Modality Area Paper Title DB J/C Year
CNN CS-MRI A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction pdf IEEE-TMI 2017
GAN CS-MRI Deep Generative Adversarial Networks for Compressed Sensing Automates MRI pdf NIPS 2017

Image synthesis for data augmentation

Technique Modality Area Paper Title DB J/C Year
GAN RGB (Microscopy) Red Blood Cells Red blood cell image generation for data augmentation using Conditional Generative Adversarial Networks [pdf] arXiv 2019
GAN MRI Brain Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks [pdf] arXiv 2018
GAN MRI Brain Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks [pdf] arXiv 2018
GAN CT, MRI Brain GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks [pdf] arXiv 2018
GAN CT Liver GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification [pdf] arXiv 2018

Other tasks

References