A Boundary-Enhanced Liver Segmentation Network for Multi-Phase CT Images with Unsupervised Domain Adaptation
Multi-phase computed tomography (CT) images have gained significant popularity in the diagnosis of hepatic disease. There are several challenges in the liver segmentation of multi-phase CT images. (1) Annotation: due to the distinct contrast enhancements observed in different phases (i.e., each phas...
Main Authors: | Swathi Ananda, Rahul Kumar Jain, Yinhao Li, Yutaro Iwamoto, Xian-Hua Han, Shuzo Kanasaki, Hongjie Hu, Yen-Wei Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
|
Series: | Bioengineering |
Subjects: | |
Online Access: | https://www.mdpi.com/2306-5354/10/8/899 |
Similar Items
-
Unsupervised Domain Adaptation in Semantic Segmentation: A Review
by: Marco Toldo, et al.
Published: (2020-06-01) -
Unsupervised Adversarial Domain Adaptation with Error-Correcting Boundaries and Feature Adaption Metric for Remote-Sensing Scene Classification
by: Chenhui Ma, et al.
Published: (2021-03-01) -
Scale variance minimization for unsupervised domain adaptation in image segmentation
by: Guan, Dayan, et al.
Published: (2022) -
Domain‐invariant adversarial learning with conditional distribution alignment for unsupervised domain adaptation
by: Xingmei Wang, et al.
Published: (2020-12-01) -
Unsupervised Transformer Boundary Autoencoder Network for Hyperspectral Image Change Detection
by: Song Liu, et al.
Published: (2023-03-01)