Deep-Learning-for-Medical-Applications
Medical Imaging Research
A curated list of deep learning papers on medical image analysis
Deep Learning Papers on Medical Image Analysis
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Deep Learning Papers on Medical Image Analysis / Table of Contents / Deep Learning Techniques | |||
| AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images | |||
| Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images | |||
| Adversarial Deep Structured Nets for Mass Segmentation from Mammograms | |||
Deep Learning Papers on Medical Image Analysis / Table of Contents / Medical Applications | |||
| [pdf] | Deep learning of feature representation with multiple instance learning for medical image analysis | ||
| [pdf] | AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images | ||
| AMIDA | |||
| Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation | |||
| [pdf] | Multi-scale Convolutional Neural Networks for Lung Nodule Classification | ||
| LIDC-IDRI | |||
| [pdf] | Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks | ||
| ADNI | |||
| [pdf] | Automatic Feature Learning to Grade Nuclear Cataracts Based on Deep Learning | ||
| [pdf] | Quantifying Radiographic Knee Osteoarthritis Severity using Deep Convolutional Neural Networks | ||
| O.E.1 | |||
| [pdf] | A Deep Semantic Mobile Application for Thyroid Cytopathology | ||
| [pdf] | Alzheimer's Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network | ||
| ADNI | |||
| [pdf] | Multi-resolution-tract CNN with hybrid pretrained and skin-lesion trained layers | ||
| Dermofit | |||
| [pdf] | Towards Automated Melanoma Screening: Exploring Transfer Learning Schemes | ||
| EDRA | , | ||
| [pdf] | Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks | ||
| LIDC-IDRI | , , | ||
| [pdf] | DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification | ||
| LIDC-IDRI | , | ||
| [pdf] | 3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients | ||
| [pdf] | Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans | ||
| LIDC-IDRI | |||
| [pdf] | Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring | ||
| [pdf] | Deep multi-instance networks with sparse label assignment for whole mammogram classification | ||
| INbreast | |||
| [pdf] | Spectral Graph Convolutions for Population-based Disease Prediction | ||
| ADNI | , | ||
| [pdf] | SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks | ||
| [pdf] | 3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data | ||
| [pdf] | Standard Plane Localization in Fetal Ultrasound via Domain Transferred Deep Neural Networks | ||
| [pdf] | Automated anatomical landmark detection ondistal femur surface using convolutional neural network | ||
| OAI | |||
| [pdf] | Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks | ||
| [pdf] | Regressing Heatmaps for Multiple Landmark Localization using CNNs | ||
| DHADS | |||
| [pdf] | An artificial agent for anatomical landmark detection in medical images | ||
| SATCOM | |||
| [pdf] | Real-time Standard Scan Plane Detection and Localisation in Fetal Ultrasound using Fully Convolutional Neural Networks | ||
| [pdf] | Recognizing end-diastole and end-systole frames via deep temporal regression network | ||
| [pdf] | Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation Neural Networks | ||
| [pdf] | Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique Neural Networks | ||
| [pdf] | Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks | ||
| [pdf] | Self-Transfer Learning for Fully Weakly Supervised Lesion Localization | ||
| NIH,China | , | ||
| [pdf] | Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images | ||
| DRD | , | ||
| [pdf] | DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification | ||
| LIDC-IDRI | , | ||
| [pdf] | DeepEM: Deep 3D ConvNets with EM for weakly supervised pulmonary nodule detection | ||
| LIDC-IDRI | , | ||
| [pdf] | Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation | ||
| [pdf] | AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy | ||
| [pdf] | Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields | ||
| [pdf] | Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks | ||
| [pdf] | SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks | ||
| [pdf] | q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI (Section II.B.2) | ||
| [pdf] | Adversarial Deep Structured Nets for Mass Segmentation from Mammograms | ||
| INbreast | , | ||
| 3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes | |||
| Unsupervised domain adaptation in brain lesion segmentation with adversarial networks | |||
| A Fully Convolutional Neural Network based Structured Prediction Approach Towards the Retinal Vessel Segmentation | |||
| [pdf] | An Artificial Agent for Robust Image Registration | ||
| [pdf] | Automated anatomical landmark detection ondistal femur surface using convolutional neural network | ||
| OAI | |||
| [pdf] | q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI (Section II.B.1) | ||
| [HCP] | and other | ||
| A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction | |||
| Deep Generative Adversarial Networks for Compressed Sensing Automates MRI | |||
| [pdf] | Red blood cell image generation for data augmentation using Conditional Generative Adversarial Networks | ||
| [pdf] | Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks | ||
| [pdf] | Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks | ||
| [pdf] | GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks | ||
| [pdf] | GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification | ||
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