Abstract
ObjectiveMany artificial intelligence approaches to muscle ultrasound image analysis have not been implemented on usable devices in clinical neuromuscular medicine practice, owing to high computational demands and lack of standardised testing protocols. This study evaluated the feasibility of using real-time texture analysis to differentiate between various pathological conditions. MethodsWe analysed 17,021 cross-sectional ultrasound images of the biceps brachii of 75 participants, including 25 each with neurogenic disorders, myogenic disorders, and healthy controls. The size and location of the regions of interest were randomly selected to minimise bias. A random forest classifier utilising texture features such as Dissimilarity and Homogeneity was developed and deployed on a mobile PC, enabling real-time analysis. ResultsThe classifier distinguished patients with an accuracy of 81 %. Echogenicity and Contrast from the Co-Occurrence Matrix were significant predictive features. Validation on 15 patients achieved accuracies of 78 %/93 % per image/patient over 15-second videos, respectively. The use of a mobile PC facilitated real-time estimation of the underlying pathology during ultrasound examination, without influencing procedures. ConclusionsReal-time automatic texture analysis is feasible as an adjunct for the diagnosis of neuromuscular disorders. SignificanceArtificial intelligence using texture analysis with a light computational load supports the semi-quantitative evaluation of neuromuscular ultrasound.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.