Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.

Authors

Toshiyuki Okada
Marius George Linguraru, George Washington UniversityFollow
Masatoshi Hori
Ronald M. Summers, George Washington University
Noriyuki Tomiyama
Yoshinobu Sato

Document Type

Journal Article

Publication Date

7-4-2015

Journal

Medical Image Analysis

Volume

26

Issue

1

Inclusive Pages

1-18

DOI

10.1016/j.media.2015.06.009

Keywords

Pattern Recognition, Automated--methods; Radiographic Image Interpretation, Computer-Assisted--methods; Radiography, Abdominal--methods; Tomography, X-Ray Computed--methods; Unsupervised Machine Learning; Viscera--radiography

APA Citation

Kada, T., Linguraru, M. G., Hori, M., Summers, R. M., Tomiyama, N., & Sato, Y. (2015). Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors. Medical Image Analysis, 26(1), 1-18.

Peer Reviewed

1