A Unified Level Set Framework Combining Hybrid Algorithms for Liver and Liver Tumor Segmentation in CT Images
Accurate and reliable segmentation of liver tissue and liver tumor is essential for the follow-up of hepatic diagnosis. In this paper, we present a method for liver segmentation and a method for liver tumor segmentation. The two methods are grounded on a novel unified level set method (LSM), which i...
Main Authors: | Zhou Zheng, Xuechang Zhang, Huafei Xu, Wang Liang, Siming Zheng, Yueding Shi |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2018-01-01
|
Series: | BioMed Research International |
Online Access: | http://dx.doi.org/10.1155/2018/3815346 |
Similar Items
-
Segmentation of liver tumors on CT images
by: Pescia, Daniel
Published: (2011) -
AHCNet: An Application of Attention Mechanism and Hybrid Connection for Liver Tumor Segmentation in CT Volumes
by: Huiyan Jiang, et al.
Published: (2019-01-01) -
Liver Tumor Segmentation in CT Scans Using Modified SegNet
by: Sultan Almotairi, et al.
Published: (2020-03-01) -
Effects of Multiple Filters on Liver Tumor Segmentation From CT Images
by: Vi Thi-Tuong Vo, et al.
Published: (2021-10-01) -
Deep Learning Initialized and Gradient Enhanced Level-Set Based Segmentation for Liver Tumor From CT Images
by: Yue Zhang, et al.
Published: (2020-01-01)