Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images.

Autor: Paolucci G; MIDA, Dipartimento di Matematica, Università di Genova, via Dodecaneso 35, Genova, 16145, Italy., Cama I; MIDA, Dipartimento di Matematica, Università di Genova, via Dodecaneso 35, Genova, 16145, Italy., Campi C; MIDA, Dipartimento di Matematica, Università di Genova, via Dodecaneso 35, Genova, 16145, Italy.; IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi 10, Genova, 16132, Italy., Piana M; MIDA, Dipartimento di Matematica, Università di Genova, via Dodecaneso 35, Genova, 16145, Italy. piana@dima.unige.it.; IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi 10, Genova, 16132, Italy. piana@dima.unige.it.
Jazyk: angličtina
Zdroj: BMC medical imaging [BMC Med Imaging] 2024 Sep 19; Vol. 24 (1), pp. 251. Date of Electronic Publication: 2024 Sep 19.
DOI: 10.1186/s12880-024-01423-0
Abstrakt: The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia, i.e. a systemic loss of skeletal muscle mass and function that may be correlated to multifactorial etiological aspects. The inclusion of sarcopenia assessment into a radiological workflow would need the implementation of computational pipelines for image processing that guarantee segmentation reliability and a significant degree of automation. The present study utilizes three-dimensional numerical schemes for psoas segmentation in low-dose X-ray computed tomography images. Specifically, here we focused on the level set methodology and compared the performances of two standard approaches, a classical evolution model and a three-dimension geodesic model, with the performances of an original first-order modification of this latter one. The results of this analysis show that these gradient-based schemes guarantee reliability with respect to manual segmentation and that the first-order scheme requires a computational burden that is significantly smaller than the one needed by the second-order approach.
(© 2024. The Author(s).)
Databáze: MEDLINE
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