Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images

Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images

Abstract Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medical images. However, current approaches were either applied only to 2D cross-sectional images, addressed few structures, or were validated on...

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Bibliographic Details
Main Authors: Mazen Soufi, Yoshito Otake, Makoto Iwasa, Keisuke Uemura, Tomoki Hakotani, Masahiro Hashimoto, Yoshitake Yamada, Minoru Yamada, Yoichi Yokoyama, Masahiro Jinzaki, Suzushi Kusano, Masaki Takao, Seiji Okada, Nobuhiko Sugano, Yoshinobu Sato
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-83793-7
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