Optimized U3-Net framework for multi-class liver and tumor segmentation: a comparative study with boundary-aware clinical metrics

Accurate segmentation of liver and tumor regions in Computed Tomography (CT) scans is fundamental for the effective diagnosis and surgical planning of hepatic malignancies. This study evaluates and compares three sophisticated Convolutional Neural Network (CNN) architectures—U-Net, U2-Net, and U3-Ne...

Полное описание

Библиографические подробности

Главные авторы:	Walaa Sameer Araydah, Ansam Basem Al-Hyarat, Abdelwadood Muhammad Mesleh, Bilal Muhammad Zahran
Формат:	Artigo
Язык:	Inglês
Опубликовано:	PeerJ Inc. 2026-05-01
Серии:	PeerJ Computer Science
Предметы:	Liver TS CT scan analysis U-Net U2-Net U3-Net Deep learning (DL)
Online-ссылка:	https://peerj.com/articles/cs-3835.pdf
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!