Cortexpert: A Model-Based Method For Automatic Renal Cortex Segmentation
Keywords
Cortex model adaptation; Non-uniform graph search; Renal cortex
Abstract
This paper introduces a model-based approach for a fully automatic delineation of kidney and cortex tissue from contrast-enhanced abdominal CT scans. The proposed framework, named CorteXpert, consists of two new strategies for kidney tissue delineation: cortex model adaptation and non-uniform graph search. CorteXpert was validated on a clinical data set of 58 CT scans using the cross-validation evaluation strategy. The experimental results indicated the state-of-the-art segmentation accuracies (as dice coefficient): 97.86% ± 2.41% and 97.48% ± 3.18% for kidney and renal cortex delineations, respectively.
Publication Date
12-1-2017
Publication Title
Medical Image Analysis
Volume
42
Number of Pages
257-273
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.media.2017.06.010
Copyright Status
Unknown
Socpus ID
85028886049 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85028886049
STARS Citation
Xiang, Dehui; Bagci, Ulas; Jin, Chao; Shi, Fei; and Zhu, Weifang, "Cortexpert: A Model-Based Method For Automatic Renal Cortex Segmentation" (2017). Scopus Export 2015-2019. 5601.
https://stars.library.ucf.edu/scopus2015/5601