Development and validation of a semi-automated and unsupervised method for femur segmentation from CT

Development and validation of a semi-automated and unsupervised method for femur segmentation from CT

Abstract Quantitative computed tomography (QCT)-based in silico models have demonstrated improved accuracy in predicting hip fractures with respect to the current gold standard, the areal bone mineral density. These models require that the femur bone is segmented as a first step. This task can be ch...

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Bibliographic Details
Main Authors: Alessandra Aldieri, Riccardo Biondi, Antonino A. La Mattina, Julia A. Szyszko, Stefano Polizzi, Daniele Dall’Olio, Nico Curti, Gastone Castellani, Marco Viceconti
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
Bone and joint enhancement filter
CT
Femur segmentation
Finite element model
Graph-cut
Semi-automated segmentation
Online Access:https://doi.org/10.1038/s41598-024-57618-6

Internet

https://doi.org/10.1038/s41598-024-57618-6

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