LHU-Net: A Lean Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Segmentation

Sadegheih, Yousef; Bozorgpour, Afshin; Azad, Reza; Kumari, Pratibha; Merhof, Dorit

doi:978-3-032-05184-4

LHU-Net: A Lean Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Segmentation

Sadegheih, Yousef ; Bozorgpour, Afshin ; Kumari, Pratibha ; Azad, Reza^RWTH* ; Merhof, Dorit (Corresponding author)

In
Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 : 28th International Conference, Daejeon, South Korea, September 23-27, 2025, Proceedings, Part XIV / James C. Gee, Daniel C. Alexander, Jaesung Hong, Juan Eugenio Iglesias, Carole H. Sudre, Archana Venkataraman, Polina Golland, Jong Hyo Kim, Jinah Park, Seiten/Artikel-Nr: 326-336

2026

Konferenz/Event:28. International Conference on Medical Image Computing and Computer Assisted Intervention , Daejeon , South Korea , MICCAI 2025 , 2025-09-23 - 2025-09-27

ImpressumCham : Springer Nature Switzerland

Umfang326-336

ISBN978-3-032-05184-4, 978-3-032-05185-1, 978-3-032-05186-8

ReiheLecture Notes in Computer Science ; 15973