Pediatric Personalized Deep Learning Models for Segmentation of Hepatoblastoma at CT and MRI.

Saved in:
Bibliographic Details
Title: Pediatric Personalized Deep Learning Models for Segmentation of Hepatoblastoma at CT and MRI.
Authors: Modanwal G; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Health Sciences Research Building II, 1750 Haygood Dr, Ste N647, Atlanta, GA 30322., Kumar S; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Health Sciences Research Building II, 1750 Haygood Dr, Ste N647, Atlanta, GA 30322., Viswanathan V; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Health Sciences Research Building II, 1750 Haygood Dr, Ste N647, Atlanta, GA 30322., Morin CE; Department of Radiology, Cincinnati Children's Hospital, Cincinnati, Ohio.; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio., Rees MA; Department of Radiology, Nationwide Children's Hospital, Columbus, Ohio., Squires JH; Department of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pa., Tang ER; Department of Radiology, Children's Hospital of Colorado, Aurora, Colo., Katzenstein HM; Nemours Children's Hospital, Wilmington, Del., Towbin AJ; Department of Radiology, Cincinnati Children's Hospital, Cincinnati, Ohio.; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio., Madabhushi A; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Health Sciences Research Building II, 1750 Haygood Dr, Ste N647, Atlanta, GA 30322.; Atlanta Veterans Administration Medical Center, Atlanta, Ga., Schooler GR; Department of Radiology, Cincinnati Children's Hospital, Cincinnati, Ohio.; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio.
Source: Radiology. Imaging cancer [Radiol Imaging Cancer] 2026 Mar; Vol. 8 (2), pp. e250041.
Publication Type: Journal Article; Multicenter Study
Journal Info: Publisher: Radiological Society of North America, Inc Country of Publication: United States NLM ID: 101765309 Publication Model: Print Cited Medium: Internet ISSN: 2638-616X (Electronic) Linking ISSN: 2638616X NLM ISO Abbreviation: Radiol Imaging Cancer Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2638-616X
DOI:10.1148/rycan.250041