Get our free extension to see links to code for papers anywhere online!

Add to Chrome

Add to Firefox

Picture for Shaoting Zhang

Shaoting Zhang

PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation

Aug 19, 2022
Guotai Wang, Xiangde Luo, Ran Gu, Shuojue Yang, Yijie Qu, Shuwei Zhai, Qianfei Zhao, Kang Li, Shaoting Zhang

Figure 1 for PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation

Figure 2 for PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation

Figure 3 for PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation

Figure 4 for PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation

* 10 pages, 5 figures

Access Paper or Ask Questions

PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation

Aug 11, 2022
Shuwei Zhai, Guotai Wang, Xiangde Luo, Qiang Yue, Kang Li, Shaoting Zhang

Figure 1 for PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation

Figure 2 for PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation

Figure 3 for PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation

Figure 4 for PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation

* 10 pages, 9 figures, 3 tables

Access Paper or Ask Questions

HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy

Jun 07, 2022
Hao Fu, Guotai Wang, Wenhui Lei, Wei Xu, Qianfei Zhao, Shichuan Zhang, Kang Li, Shaoting Zhang

Figure 1 for HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy

Figure 2 for HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy

Figure 3 for HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy

Figure 4 for HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy

* 11 pages, 6 figures, Accepted by IEEE JBHI

Access Paper or Ask Questions

Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation

May 13, 2022
Ran Gu, Jiangshan Lu, Jingyang Zhang, Wenhui Lei, Xiaofan Zhang, Guotai Wang, Shaoting Zhang

Figure 1 for Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation

Figure 2 for Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation

Figure 3 for Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation

Figure 4 for Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation

* 10 pages, 2 figures

Access Paper or Ask Questions

Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

Mar 04, 2022
Xiangde Luo, Minhao Hu, Wenjun Liao, Shuwei Zhai, Tao Song, Guotai Wang, Shaoting Zhang

Figure 1 for Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

Figure 2 for Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

Figure 3 for Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

Figure 4 for Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

* 11 pages, 4 figures,code is available: https://github.com/HiLab-git/WSL4MIS.This is a comprehensive study about scribble-supervised medical image segmentation based on the ACDC dataset

Access Paper or Ask Questions

Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

Dec 09, 2021
Xiangde Luo, Minhao Hu, Tao Song, Guotai Wang, Shaoting Zhang

Figure 1 for Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

Figure 2 for Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

Figure 3 for Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

Figure 4 for Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

* A technical report about SSL4MIS:https://github.com/HiLab-git/SSL4MIS

Access Paper or Ask Questions