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

Radiology Imaging Cancer 2026 Open access

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Authors: Gourav Modanwal, Saurabh Kumar, Vidya Sankar Viswanathan, Cara E. Morin, Mitchell A. Rees, J. E. Squires, Elizabeth R. Tang, Howard M. Katzenstein, Alexander J. Towbin, Anant Madabhushi, Gary R. Schooler
DOI: 10.1148/rycan.250041
Cited by: 1
References: 37

Abstract

Deep learning–based hepatoblastoma segmentation models trained on pediatric CT and MRI scans demonstrated good agreement with human annotators and their consensus. Pediatric contrast-enhanced CT model outperformed the adult CT-trained model.

Fields of Study & Subjects

Hepatocellular Carcinoma Treatment and Prognosis Advanced Radiotherapy Techniques Genetic and Kidney Cyst Diseases

Publication details

Journal / source
Radiology Imaging Cancer
Publisher
Radiological Society of North America (RSNA)
Volume
8
Issue
2
Pages
e250041–e250041
Publication date
20 February 2026
Language
EN