Finding Reproducible and Prognostic Radiomic Features in Variable Slice Thickness Contrast Enhanced CT of Colorectal Liver Metastases.

Saved in:
Bibliographic Details
Title: Finding Reproducible and Prognostic Radiomic Features in Variable Slice Thickness Contrast Enhanced CT of Colorectal Liver Metastases.
Authors: Peoples JJ; School of Computing, Queen's University, Kingston, ON, Canada., Hamghalam M; School of Computing, Queen's University, Kingston, ON, Canada.; Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran., James I; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Wasim M; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Gangai N; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Kang HC; Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Rong XJ; Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Chun YS; Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Do RKG; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Simpson AL; School of Computing, Queen's University, Kingston, ON, Canada.; Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada.
Source: The journal of machine learning for biomedical imaging [J Mach Learn Biomed Imaging] 2025; Vol. 2 (UNSURE2023), pp. 2326-2357. Date of Electronic Publication: 2025 Jan 15.
Publication Type: Journal Article
Journal Info: Publisher: MELBA Country of Publication: United States NLM ID: 9918400085306676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2766-905X (Electronic) Linking ISSN: 2766905X NLM ISO Abbreviation: J Mach Learn Biomed Imaging Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2766-905X
DOI:10.59275/j.melba.2024-24gc