In the last few years, there has been an increasing interest in the role of deep fascia mobility in musculoskeletal dynamics and chronic pain mechanisms. In a previous paper we presented an innovative semiautomatic approach to evaluate the 3D motion of the fascia using ultrasound (US) imaging, generating a sparse deformation vector field. This paper presents an improvement of our original method, focusing on the filtering of the sparse vector field and its validation. Moreover, in order to evaluate the performance of the algorithm, a method is proposed to generate synthetic deformation vector fields, including: expansion, rotation, horizontal shear, and oblique shear components. Preliminary tests on the final synthetic deformation vector fields showed promising results. Further experiments are required in order to optimize the tuning of the algorithm.

A 3D sparse motion field filtering for quantitative analysis of fascial layers mobility based on 3D ultrasound scans

TURINI, GIUSEPPE;CONDINO, SARA;FERRARI, VINCENZO;FERRARI, MAURO;GESI, MARCO
2015-01-01

Abstract

In the last few years, there has been an increasing interest in the role of deep fascia mobility in musculoskeletal dynamics and chronic pain mechanisms. In a previous paper we presented an innovative semiautomatic approach to evaluate the 3D motion of the fascia using ultrasound (US) imaging, generating a sparse deformation vector field. This paper presents an improvement of our original method, focusing on the filtering of the sparse vector field and its validation. Moreover, in order to evaluate the performance of the algorithm, a method is proposed to generate synthetic deformation vector fields, including: expansion, rotation, horizontal shear, and oblique shear components. Preliminary tests on the final synthetic deformation vector fields showed promising results. Further experiments are required in order to optimize the tuning of the algorithm.
2015
9781424492718
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/768322
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