1. 2019 綜述閱讀 醫(yī)學(xué)+深度 2019--Going Deep in Medical Image Analysis:Concepts, Methods, Challenges and Future Directions
圖片語(yǔ)義分割深度學(xué)習(xí)算法要點(diǎn)回顧
2019 圖像分割算法最佳綜述
2. Understanding Deep Learning Techniques for Image Segmentation
3. Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation
4. Deep Semantic Segmentation of Natural and Medical Images: A Review
5. Deep learning for cardiac image segmentation: A review
6. Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications
大腦綜述 2017
7. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions
TMI 2019
https://dblp.uni-trier.de/db/journals/tmi/
8.Multiple Resolution Residually Connected Feature Streams for Automatic Lung Tumor Segmentation From CT Images
9. Transfer Learning for Image Segmentation by Combining Image Weighting and Kernel Learning
10. Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning
11.Medical Image Imputation From Image Collections
12. HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation
13. Splenomegaly Segmentation on Multi-Modal MRI Using Deep Convolutional Networks
MICCAI 2019
https://dblp.uni-trier.de/db/conf/miccai/
14. One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation
15. Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation
16. HD-Net: Hybrid Discriminative Network for Prostate Segmentation in MR Images
17. Liver Segmentation in Magnetic Resonance Imaging via Mean Shape Fitting with Fully Convolutional Neural Networks
18. Multi-scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma
19. PAN: Projective Adversarial Network for Medical Image Segmentation
20. Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Images
21. Integrating Cross-modality Hallucinated MRI with CT to Aid Mediastinal Lung Tumor Segmentation
22. Normal Appearance Autoencoder for Lung Cancer Detection and Segmentation
23. NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation
24. Pulmonary Vessel Segmentation Based on Orthogonal Fused U-Net++ of Chest CT Images
25. Harnessing 2D Networks and 3D Features for Automated Pancreas Segmentation from Volumetric CT Images
26. LVC-Net: Medical Image Segmentation with Noisy Label Based on Local Visual Cues
27. Anatomical Priors for Image Segmentation via Post-processing with Denoising Autoencoders
28. Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization
29.Advancing Pancreas Segmentation in Multi-protocol MRI Volumes Using Hausdorff-Sine Loss Function
30. End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation
31. Privacy-Preserving Federated Brain Tumour Segmentation
32. Automatic Couinaud Segmentation from CT Volumes on Liver Using GLC-UNet
33. A Hybrid Multi-atrous and Multi-scale Network for Liver Lesion Detection
34. Deep Learning Model Integrating Dilated Convolution and Deep Supervision for Brain Tumor Segmentation in Multi-parametric MRI
35. A Joint 3D UNet-Graph Neural Network-Based Method for Airway Segmentation from Chest CTs
ISBI 2019
https://dblp.uni-trier.de/db/conf/isbi/
