Paper Info
Title
Bridging the Gap Between 2D and 3D Contexts in CT Volume for Liver and Tumor Segmentation
Abstract
Automatic liver and tumor segmentation remain a challenging topic, which subjects to the exploration of 2D and 3D contexts in CT volume. Existing methods are either only focus on the 2D context by treating the CT volume as many independent image slices (but ignore the useful temporal information between adjacent slices), or just explore the 3D context lied in many little voxels (but damage the spa...
Year
DOI
Venue
2021
10.1109/JBHI.2021.3075752
IEEE Journal of Biomedical and Health Informatics
Keywords
DocType
Volume
Liver,Tumors,Computed tomography,Three-dimensional displays,Feature extraction,Bioinformatics,Lesions
Journal
25
Issue
ISSN
Citations 
9
2168-2194
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Lei Song100.34
Wang H27129.35
Z Jane Wang381.20