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Journal of Biomedical Optics

Neuromuscular disease classification system
Author(s): Aurora Sáez; Begoña Acha; Adoración Montero-Sánchez; Eloy Rivas; Luis M. Escudero; Carmen Serrano
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Paper Abstract

Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

Paper Details

Date Published: 26 June 2013
PDF: 13 pages
J. Biomed. Opt. 18(6) 066017 doi: 10.1117/1.JBO.18.6.066017
Published in: Journal of Biomedical Optics Volume 18, Issue 6
Show Author Affiliations
Aurora Sáez, Univ. de Sevilla (Spain)
Begoña Acha, Univ. de Sevilla (Spain)
Adoración Montero-Sánchez, Consejo Superior de Investigaciones Científicas (Spain)
Eloy Rivas, Consejo Superior de Investigaciones Científicas (Spain)
Luis M. Escudero, Consejo Superior de Investigaciones Científicas (Spain)
Carmen Serrano, Univ. de Sevilla (Spain)

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