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Título : Tissue discrimination in magnetic resonance imaging of the rator cuff
metadata.dc.creator: Ballarín, Virginia L.
Meschino, Gustavo
Capiel, Carlos
Comas, Diego S.
Palabras clave : Informática y Salud
metadata.dc.date: 2016
Editorial : Universidad FASTA. Facultad de Ingeniería
Descripción : Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients' health.
Fil: Meschino, Gustavo. Universidad FASTA. Facultad de Ingeniería; Argentina.
Fil: Capiel, Carlos. Universidad FASTA. Facultad de Ingeniería; Argentina.
Fil: Comas, Diego S. Universidad FASTA. Facultad de Ingeniería; Argentina.
Fil: Ballarín, Virginia L. Universidad FASTA. Facultad de Ingeniería; Argentina.
URI : http://redi.ufasta.edu.ar:8082/jspui/handle/123456789/1211
Aparece en las colecciones: Facultad de Ingeniería - G.I - Informática y Salud

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