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2. Papers- 医学图像分析.md

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[toc]

==Review and Survey==

  • 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]

Computed Tomography (CT)

2015

  • 3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data MICCAI 2015 [paper]

2016

  • 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]

2017

  • 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]

2018

  • 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]

Magnetic Resonance Imaging (MRI)

2016

  • 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]
  • Regressing Heatmaps for Multiple Landmark Localization Using CNNs MICCAI 2016 [paper]

2017

  • 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]
  • Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets
  • 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]
  • Boundary-Aware Fully Convolutional Network for Brain Tumor Segmentation MICCAI 2017 [paper]

2018

  • 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]

Ultrasound (US)

2015

  • Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks [paper]

2016

  • 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]

2017

  • 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]

2018

  • 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 TBME 2018 [paper]

X-ray

2015

  • Deep Learning and Structured Prediction for the Segmentation of Mass in Mamograms MICCAI 2015 [paper]

2016

  • Learning to Read Chest X-Rays Recurrent Neural Cascade Model for Automated Image Annotation 2016 [paper]

2017

  • Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks [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]
  • 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]

2018

  • SCAN Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays [paper]
  • Fully Convolutional Architectures for Multiclass Segmentation in Chest Radiographs TMI 2018 [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]

PET

2017

  • 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]

Funduscopy

2016

  • DeepVessel Retinal Vessel Segmentation via Deep Learning and Conditional Random Field MICCAI 2016 [paper]

2017

  • Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks [paper] [Keras+TF code]

2018

  • 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]

Microscopy

2016

  • Stain Normalization Using Sparse AutoEncoders (StaNoSA) Application to Digital Pathology [paper]
  • Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images [paper]

2017

  • 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]

2018

  • 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]

Colonoscopy

2016

  • Convolutional Neural Networks for Medical Image Analysis Full Training or Fine Tuning TMI 2016 [papr]

2018

  • Real-Time Polyps Segmentation for Colonoscopy Video Frames Using Compressed Fully Convolutional Network [paper]

OCT

2017

  • Cystoid Macular Edema Segmentation of Optical Coherence Tomography Images Using Fully Convolutional Neural Networks and Fully Connected CRFs 2017 [paper]

Dermoscopy

2016

  • 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]

2017

  • 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)"
  • Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks [paper]
  • Dermoscopic Image Segmentation via Multi-Stage Fully Convolutional Networks [paper]
  • Skin melanoma segmentation using recurrent and convolutional neural networks [paper]
  • Skin Lesion Classification Using Hybrid Deep Neural Networks 2017 [paper]

2018

  • DermoNet Densely Linked Convolutional Neural Network for Efficient Skin Lesion Segmentation [paper]
  • Techniques and Algorithms for Computer Aided Diagnosis of Pigmented Skin Lesions A Review [paper]
  • MelanoGANs High Resolution Skin Lesion Synthesis with GANs [paper]
  • SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks MICCAI 2018 [paper]
  • Skin Lesion Classification with Ensemble of Squeeze-and-excitation Networks and Semi-supervised Learning 2018 [paper]

Endoscopy

2018

  • Articulated Multi-Instrument 2-D Pose Estimation Using Fully Convolutional Networks 2018 [paper] [code]