Guest Editorial Deep Learning in Medical Imaging Overview and Future Promise of an Exciting New Technique 2016 [paper]
Overview of Deep Learning in Medical Imaging 2017 [paper]
A Survey on Deep Learning in Medical Image Analysis 2017 [paper]
Deep Learning Applications in Medical Image Analysis 2017 [paper]
Deep Learning in Medical Image Analysis 2017 [paper]
Deep Learning in Microscopy Image Analysis A Survey 2017 [paper]
GANs for Medical Image Analysis 2018 [paper]
Generative Adversarial Network in Medical Imaging A Review 2018 [paper]
Deep Learning in Medical Image Registration A Survey 2019 [paper]
Deep Learning in Medical Ultrasound Analysis A Review Engineering 2019 [paper]
Deep Learning in Cardiology 2019 [paper]
Deep learning in Medical Imaging and Radiation Therapy MP 2019 [paper]
Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges JDI 2019 [paper]
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation arXiv [paper]
Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications arXiv [paper]
Development of a Digital Image Database for Chest Radiographs with and without a Lung Nodule AJR 2000
"Chest Radiographs", "the JSRT database"
Segmentation of Anatomical Structures in Chest Radiographs Using Supervised Methods A Comparative Study on a Public Database MedIA 2006
"Chest Radiographs", "the SCR dataset (ground-truth segmentation masks) for the JSRT database (X-ray images)"
ChestX-ray8 Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases CVPR 2017 [dataset]
"Chest Radiographs"
KiTS 2019 [dataset]
"300 Abdomen CT scans for kidney and tumor segmentation"
CHD_Segmentation [dataset]
"68 CT images with labels. The label includes left ventricle, right ventricle, left atrium, right atrium, myocardium, aorta, and pulmonary artery."
3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data MICCAI 2015 [paper]
Low-dose CT Denoising with Convolutional Neural Network [paper]
Low-Dose CT via Deep Neural Network [paper]
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks [paper]
Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields MICCAI 2016 [paper]
"CRF"
An Artificial Agent for Anatomical Landmark Detection in Medical Images MICCAI 2016 [paper]
"deep reinforcement learning", "anatomical landmark detection"
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss [paper]
Automatic Liver Segmentation Using an Adversarial Image-to-Image Network MICCAI 2017 [paper]
Sharpness-aware Low Dose CT Denoising Using Conditional Generative Adversarial Network [paper]
Framing U-Net via Deep Convolutional Framelets: Application to Sparse-view CT [paper]
Deep Embedding Convolutional Neural Network for Synthesizing CT Image from T1-Weighted MR Image [paepr]
A Self-aware Sampling Scheme to Efficiently Train Fully Convolutional Networks for Semantic Segmentation [paper]
DeepLesion Automated Deep Mining Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion Annotations [paper]
Unsupervised End-to-end Learning for Deformable Medical Image Registration [paper]
DeepLung 3D Deep Convolutional Nets for Automated Pulmonary Nodule Detection and Classification [paper]
CT Image Denoising with Perceptive Deep Neural Networks [paper]
Improving Low-Dose CT Image Using Residual Convolutional Network [paper]
Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN) [paper]
Stacked Competitive Networks for Noise Reduction in Low-dose CT [paper]
Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisy-or Network [paper]
Robust Landmark Detection in Volumetric Data with Efficient 3D Deep Learning [paper]
Robust Multi-scale Anatomical Landmark Detection in Incomplete 3D-CT Data [paper]
Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans TPAMI 2017 [paper]
DeepLung Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification [paper]
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans [paper]
Attention U-Net Learning Where to Look for the Pancreas [paper]
Calcium Removal From Cardiac CT Images Using Deep Convolutional Neural Network [paper]
3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network [paper]
Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network [paper]
Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising [paper]
Towards Intelligent Robust Detection of Anatomical Structures in Incomplete Volumetric Data MedIA 2018 [paper]
Partial Policy-based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images Arxiv 2018 [paper]
"reinforcement learning", "anatomical landmark localization", "aortic valve". "left atrial appendage"
Deeply Self-Supervising Edge-to-Contour Neural Network Applied to Liver Segmentation [paper]
Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network CVPR 2018 [paper]
AnatomyNet: Deep 3D Squeeze-and-excitation U-Nets for fast and fully automated whole-volume anatomical segmentation [paper]
DeepEM Deep 3D ConvNets With EM For Weakly Supervised Pulmonary Nodule Detection MICCAI 2018 [paper]
Computation of Total Kidney Volume from CT images in Autosomal Dominant Polycystic Kidney Disease using Multi-Task 3D Convolutional Neural Networks 2018 [paper]
Btrfly Net: Vertebrae Labelling with Energy-based Adversarial Learning of Local Spine Prior [paper]
Deep Learning Based Rib Centerline Extraction and Labeling [paper]
Liver Lesion Detection from Weakly-Labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector MICCAI 2018 [paper]
CFUN: Combining Faster R-CNN and U-net Network for Efficient Whole Heart Segmentation 2018 [paper]
Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database CVPR 2018 [paper]
3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas CR 2018 [paper]
Efficient Multiple Organ Localization in CT Image using 3D Region Proposal Network IEEE TMI 2019 [paper]
Medical Image Synthesis with Context-aware Generative Adversarial Networks [paper]
Multi-scale and Modality Dropout Learning for Intervertebral Disc Localization and Segmentation [paper]
Pancreas Segmentation in MRI Using Graph-Based Decision Fusion on Convolutional Neural Networks MICCAI 2016 [paper]
"CRF"
Regressing Heatmaps for Multiple Landmark Localization Using CNNs MICCAI 2016 [paper]
"Multiple Landmark Localization"
SegAN Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation [paper]
Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images [paper]
Deep MR to CT Synthesis using Unpaired Data [paper]
Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT [paper]
3D Fully Convolutional Networks for Subcortical Segmentation in MRI A Large-scale Study [paper] [code]
2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation [paper]
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI [paper]
Texture and Structure Incorporated ScatterNet Hybrid Deep Learning Network (TS-SHDL) For Brain Matter Segmentation [paper]
Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks [paper]
Deep Learning with Domain Adaptation for Accelerated Projection Reconstruction MR [paper]
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction [paper]
Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks [paper]
Learning a Variational Network for Reconstruction of Accelerated MRI Data [paper]
A Parallel MR Imaging Method Using Multilayer Perceptron [paper]
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction [paper]
Image Reconstruction by Domain Transform Manifold Learning [paper]
Human-level CMR Image Analysis with Deep Fully Convolutional Networks [paper]
A Novel Automatic Segmentation Method to Quantify the Effects of Spinal Cord Injury on Human Thigh Muscles and Adipose Tissue MICCAI 2017 [paper]
"CRF"
Boundary-Aware Fully Convolutional Network for Brain Tumor Segmentation MICCAI 2017 [paper]
"CRF"
Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks [paper]
3D Multi-scale FCN with Random Modality Voxel Dropout Learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images [paper]
Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network [paper]
Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks [paper]
k-Space Deep Learning for Accelerated MRI [paper]
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation [paper]
Deformable Image Registration Using a Cue-Aware Deep Regression Network TBME 2018 [paper]
Multi-Views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images TBME 2018 [paper]
3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes MICCAI 2018 [paper]
"focal loss", "Exponential Logarithmic Loss"
Whole Heart and Great Vessel Segmentation with Context-aware of Generative Adversarial Networks 2018 [paper]
An Unsupervised Learning Model for Deformable Medical Image Registration CVPR 2018 [paper]
VoxelMorph: A Learning Framework for Deformable Medical Image Registration IEEE TMI 2018 [paper]
Direct delineation of myocardial infarction without contrast agents using a joint motion feature learning architecture MedIA 2018 [paper]
Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network IEEE TMI 2019 [paper]
Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks [paper]
Stacked Deep Polynomial Network Based Representation Learning for Tumor Classification with Small Ultrasound Image Dataset [paper]
Real-time Detection and Localisation of Fetal Standard Scan Planes in 2D Freehand Ultrasound 2016 [paper]
Real-time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks 2016 [paper]
Describing Ultrasound Video Content Using Deep Convolutional Neural Networks 2016 [paper]
Convolutional Neural Networks for Medical Image Analysis Full Training or Fine Tuning [paepr]
Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks [paper]
Simulating Patho-realistic Ultrasound Images using Deep Generative Networks with Adversarial Learning [paper]
Anatomically Constrained Neural Networks (ACNN) Application to Cardiac Image Enhancement and Segmentation [paper]
Hough-CNN Deep learning for segmentation of deep brain regions in MRI and ultrasound CVIU 2017 [paper]
Cascaded Fully Convolutional Networks for Automatic Prenatal Ultrasound Image Segmentation 2017 [paper]
Ultrasound Standard Plane Detection Using a Composite Neural Network Framework 2017 [paper]
CNN-based Estimation of Abdominal Circumference from Ultrasound Images 2017 [paper]
Automatic Fetal Head Circumference Measurement in Ultrasound Using Random Forest and Fast Ellipse Fitting [paper]
Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks [paper]
Cascaded Transforming Multi-task Networks For Abdominal Biometric Estimation from Ultrasound [paepr]
Adversarial Image Registration with Application for MR and TRUS Image Fusion 2018 [paper]
Fully Automatic Myocardial Segmentation of Contrast Echocardiography Sequence Using Random Forests Guided by Shape Model 2018 [paper]
High Frame-rate Cardiac Ultrasound Imaging with Deep Learning MICCAI 2018 [paper]
High Quality Ultrasonic Multi-line Transmission through Deep Learning MICCAI 2018 [paper]
Deep Adversarial Context-Aware Landmark Detection for Ultrasound Imaging 2018 [paper]
Weakly Supervised Localisation for Fetal Ultrasound Images DLMIAW 2018 [paper]
Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network 2018 [paper]
Less is More Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images 2018 [paper]
Attention-Gated Networks for Improving Ultrasound Scan Plane Detection 2018 [paper]
A Radiomics Approach With CNN for Shear-Wave Elastography Breast Tumor Classification IEEE TBME 2018 [paper]
Identification of Metastatic Lymph Nodes in MR Imaging with Faster Region-Based Convolutional Neural Networks CR 2018 [paper]
Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation IEEE TMI 2018 [[paper]](Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation)
Deep Learning and Structured Prediction for the Segmentation of Mass in Mamograms MICCAI 2015 [paper]
Learning to Read Chest X-Rays Recurrent Neural Cascade Model for Automated Image Annotation 2016 [paper]
Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks DLMIA 2017 [paper]
Abnormality Detection and Localization in Chest X-Rays using Deep Convolutional Neural Networks [paper]
Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks 2017 [paper]
"reimplement this recently", "segmentation data for normalization was done"
Cascade of Multi-scale Convolutional Neural Networks for Bone Suppression of Chest Radiographs in Gradient Domain 2017 [paper]
CheXNet Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning 2017 [paper]
Adversarial Deep Structural Networks for Mammographic Mass Segmentation MICCAI 2017 [paper]
Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification MICCAI 2017 [paper]
A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification 2017 [paper]
High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks 2017 [paper]
Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning TMI 2017 [paper]
"focus on this recently (20181001)"
SCAN Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays [paper]
Fully Convolutional Architectures for Multiclass Segmentation in Chest Radiographs IEEE TMI 2018 [TMI paper] [ArXiv paper]
Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation 2018 [paper]
LF-SegNet A Fully Convolutional Encoder–Decoder Network for Segmenting Lung Fields from Chest Radiographs 2018 [paper]
Learning to Recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks 2018 [paper]
Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification 2018 [paper]
Breast Mass Segmentation and Shape Classification in Mammograms Using Deep Neural Networks [paper]
"conditional generative adversarial networks", "INbreast", "digital database for screening mammography (DDSM)"
Medical Image Description Using Multi-task-loss CNN 2016 [paper]
Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification MICCAI 2018 [paper]
Benign and malignant breast tumors classification based on region growing and CNN segmentation ESA 2015 [paper]
Adversarial Deep Structured Nets for Mass Segmentation from Mammograms ISBI 2018 [paper]
Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net MICCAI 2018 [paper]
Thoracic Disease Identification and Localization with Limited Supervision CVPR 2018 [paper]
Weakly Supervised Medical Diagnosis and Localization from Multiple Resolutions 2018 [paper]
Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning CBM 2018 [paper]
Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder RAMBO 2018 [paper]
Learning to detect chest radiographs containing pulmonary lesions using visual attention networks MedIA 2019 [paper]
Virtual PET Images from CT Data Using Deep Convolutional Networks Initial Results [paper]
Combo Loss Handling Input and Output Imbalance in Multi-Organ Segmentation Arxiv 2018 [paper]
Iterative PET Image Reconstruction Using Convolutional Neural Network Representation IEEE TMI 2018 [paper]
PET Image Reconstruction Using Deep Image Prior IEEE TMI 2018 [paper]
DeepVessel Retinal Vessel Segmentation via Deep Learning and Conditional Random Field MICCAI 2016 [paper]
"CRF"
Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks [paper] [Keras+TF code]
Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation TBME 2018 [paper]
Joint Optic Disc and Cup Segmentation Based on Multi-label Deep Network and Polar Transformation TMI 2018 [paper]
CE-Net: Context Encoder Network for 2D Medical Image Segmentation IEEE TMI 2019 [paper]
Stain Normalization Using Sparse AutoEncoders (StaNoSA) Application to Digital Pathology [paper]
Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images [paper]
Adversarial Image Alignment and Interpolation [paper]
CNN Cascades for Segmenting Whole Slide Images of the Kidney [paper]
Learning to Segment Breast Biopsy Whole Slide Images [paper]
SFCN-OPI Detection and Fine-grained Classification of Nuclei Using Sibling FCN with Objectness Prior Interaction [paper]
MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network CVPR 2017 [paper]
Deep Learning Framework for Multi-class Breast Cancer Histology Image Classification ICIAR 2018 [paper]
Cancer Metastasis Detection With Neural Conditional Random Field MIDL 2018 [paper]
DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks MedIA 2018 [paper]
Weakly supervised mitosis detection in breast histopathology images using concentric loss MedIA 2019 [paper]
Convolutional Neural Networks for Medical Image Analysis Full Training or Fine Tuning TMI 2016 [papr]
Real-Time Polyps Segmentation for Colonoscopy Video Frames Using Compressed Fully Convolutional Network [paper]
Cystoid Macular Edema Segmentation of Optical Coherence Tomography Images Using Fully Convolutional Neural Networks and Fully Connected CRFs 2017 [paper]
Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks [paper]
Hybrid dermoscopy image classification framework based on deep convolutional neural network and Fisher vector [paper]
Automatic melanoma detection via multi-scale lesion-biased representation and joint reverse classification [paper]
Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks with Jaccard Distance [paper]
"Jaccard distance on one hand, is similar to the known Dice overlap coefficient (also a novel loss function in V-Net), on the other hand, in the above paper, is a novel loss function suitable for binary class segmentation task. obviously, Jaccard distance is similar to IoU (intersection over union), a strict metric in object/semantic segmentation in computer vision."
Investigating deep side layers for skin lesion segmentation [paper]
Skin Lesion Segmentation via Deep RefineNet [paper]
Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks [paper]
Segmentation of dermoscopy images based on fully convolutional neural network [paper]
Multi-class Semantic Segmentation of Skin Lesions via Fully Convolutional Networks [paper]
"Multi-class (classification and segmentation)"