Cargando…
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...
Autores principales: | Zheng, Zhou, Zhang, Xuechang, Xu, Huafei, Liang, Wang, Zheng, Siming, Shi, Yueding |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6106976/ https://www.ncbi.nlm.nih.gov/pubmed/30159326 http://dx.doi.org/10.1155/2018/3815346 |
Ejemplares similares
-
A hybrid approach based on deep learning and level set formulation for liver segmentation in CT images
por: Gong, Zhaoxuan, et al.
Publicado: (2021) -
Deep learning and level set approach for liver and tumor segmentation from CT scans
por: Alirr, Omar Ibrahim
Publicado: (2020) -
A unified framework for shape segmentation, representation, and recognition
por: Malladi, R, et al.
Publicado: (1994) -
A Unified Framework for Brain Segmentation in MR Images
por: Yazdani, S., et al.
Publicado: (2015) -
RDCTrans U-Net: A Hybrid Variable Architecture for Liver CT Image Segmentation
por: Li, Lingyun, et al.
Publicado: (2022)