dc.creator | Sáez Manzano, Aurora | es |
dc.creator | Acha Piñero, Begoña | es |
dc.creator | Montero, Sánchez, Adoración | es |
dc.creator | Rivas, Eloy | es |
dc.creator | Escudero Cuadrado, Luis María | es |
dc.creator | Serrano Gotarredona, María del Carmen | es |
dc.date.accessioned | 2017-04-06T16:26:20Z | |
dc.date.available | 2017-04-06T16:26:20Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Sáez Manzano, A., Acha Piñero, B., Montero, S., Rivas, E., Escudero Cuadrado, L.M. y Serrano Gotarredona, M.d.C. (2013). Neuromuscular disease classification system. Journal of Biomedical Optics, 18 (6), 066017-1-066017-13. | |
dc.identifier.issn | 10833668 | es |
dc.identifier.uri | http://hdl.handle.net/11441/57297 | |
dc.description.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 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Spie-soc photo-optical instrumentation engineers | es |
dc.relation.ispartof | Journal of Biomedical Optics, 18 (6), 066017-1-066017-13. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Segmentation | es |
dc.subject | Watershed | es |
dc.subject | Fuzzy classification | es |
dc.subject | Feature extraction | es |
dc.subject | Neuromuscular disease | es |
dc.subject | Graph theory | es |
dc.title | Neuromuscular disease classification system | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Biología Celular | es |
dc.relation.publisherversion | http://biomedicaloptics.spiedigitallibrary.org/article.aspx?articleid=1701023 | es |
dc.identifier.doi | 10 .1117/1.JBO.18.6.066017 | es |
idus.format.extent | 13 p. | es |
dc.journaltitle | Journal of Biomedical Optics | es |
dc.publication.volumen | 18 | es |
dc.publication.issue | 6 | es |
dc.publication.initialPage | 066017-1 | es |
dc.publication.endPage | 066017-13 | es |