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

• URL: http://arxiv.org/abs/2312.05887v1
• Date: Sun, 10 Dec 2023 13:37:39 GMT
• Title: Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images
• Authors: Giulio Paolucci, Isabella Cama, Cristina Campi, Michele Piana
• Abstract summary: The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia. The present study utilizes three-dimensional numerical schemes for psoas segmentation in low-dose X-ray computed tomography images.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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