Uncertainty-aware deep co-training for semi-supervised medical image segmentation

Xu Zheng; Chong Fu; Haoyu Xie; Jialei Chen; Xingwei Wang; Chiu‐Wing Sham

doi:10.1016/j.compbiomed.2022.106051

ScienceGate Book Chapters

JOURNAL ARTICLE

Uncertainty-aware deep co-training for semi-supervised medical image segmentation

Xu Zheng Chong Fu Haoyu Xie Jialei Chen Xingwei Wang Chiu‐Wing Sham

Year: 2022 Journal: Computers in Biology and Medicine Vol: 149 Pages: 106051-106051 Publisher: Elsevier BV

DOI: 10.1016/j.compbiomed.2022.106051

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Artificial intelligence Machine learning Consistency (knowledge bases) Semi-supervised learning Segmentation Labeled data Process (computing) Supervised learning Unsupervised learning Deep learning Artificial neural network

Metrics

Cited By

4.70

FWCI (Field Weighted Citation Impact)

Refs

0.95

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

COVID-19 diagnosis using AI

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Uncertainty-aware deep co-training for semi-supervised medical image segmentation

Metrics

Citation History

Topics

Related Documents

Uncertainty-Aware Cross-Training for Semi-Supervised Medical Image Segmentation

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

Evidence-based uncertainty-aware semi-supervised medical image segmentation

Deep co-training for semi-supervised image segmentation

Boundary-Aware Uncertainty Suppression for Semi-Supervised Medical Image Segmentation