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

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 challenging...

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Bibliographic Details
Published in:	Scientific reports Vol. 14; no. 1; pp. 7403 - 13
Main Authors:	Aldieri, Alessandra, Biondi, Riccardo, La Mattina, Antonino A., Szyszko, Julia A., Polizzi, Stefano, Dall’Olio, Daniele, Curti, Nico, Castellani, Gastone, Viceconti, Marco
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 28.03.2024 Nature Publishing Group Nature Portfolio
Subjects:	639/166 639/166/985 692/700/1421/2770 Algorithms Automation Bone and joint enhancement filter Bone mineral density Computed tomography Femur Femur - diagnostic imaging Femur segmentation Finite element model Fractures Graph-cut Hip Hip Fractures - diagnostic imaging Humanities and Social Sciences Humans Image processing Image Processing, Computer-Assisted - methods Lower Extremity multidisciplinary Risk assessment Science Science (multidisciplinary) Segmentation Semi-automated segmentation Tomography, X-Ray Computed - methods Bone and joint enhancement filter Graph-cut CT Finite element model Femur segmentation Semi-automated segmentation
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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