Acmenwangtuo / Awesome-paperlist-ETVP

Awesome Paper-ETVP

Collect papers for ETVPers.

Survey

• A SURVEY ON SHAPE-CONSTRAINT DEEP LEARNING FOR MEDICAL IMAGE SEGMENTATION[paper] - 2021.01.26

Workshop

• Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training[paper] [code]
• Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images[paper]
• Modified VGG16 Network for Medical Image Analysis[video]

2021.1.26

• [Semantic Segmentation, Performance Evaluation] Rethinking Semantic Segmentation Evaluation for Explainability and Model Selection [paper]
• [U-Net, image segmentation] ANALYSIS OF INFORMATION FLOW THROUGH U-NETS[paper]

2021.1.29

• [Bottleneck ,Tansformer] Bottleneck Transformers for Visual Recognition [paper] [code]

2021.1.30

• [Tokens-to-Token,ViT] Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet[paper] [code]

2021.2.3

• [Self-supervised learning ,Nuclei instance segmentation] Instance-Aware Self-supervised Learning for Nuclei Segmentation[paper]
• [MIL] Multiple Instance Learning with Center Embeddings for Histopathology Classification[paper]
• [Self-supervision,Attention models] Self-supervised Nuclei Segmentation in Histopathological Images Using Attention[paper] [code]

2021.2.4

• [Attention,Segmentation] Squeeze-and-Attention Networks for Semantic Segmentation [paper] [code]

2021.2.17

• [Transformer,UNet] TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation[paper] [code]

• [Computational pathology,Multi-resolution] HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images[paper] [code]

• **[Active Learning] ** Diminishing Uncertainty within the Training Pool:

  Active Learning for Medical Image Segmentation [paper]

• [Interpretable,CAM] Interpretable multimodal fusion networks reveal mechanisms of brain cognition [paper]

Thanks the template from Awesome-Crowd-Counting