Use of fuzzy techniques for detection of multiple sclerosis small lesions.

Aymerich, F. Xavier, et al. "Use of fuzzy techniques for detection of multiple sclerosis small lesions.." Mathware and Soft Computing 5.2-3 (1998): 355-363. <http://eudml.org/doc/39159>.

@article{Aymerich1998,
abstract = {This work shows an application of algorithms in which fuzzy techniques are used. It is focused on the automation of image analysis for use with a non-invasive technique, as magnetic resonance, in multiple sclerosis patients, and specifically in detection of the smallest lesions. The typical uncertainty in the definition of these lesions lead us to consider that a fuzzy approach is a good solution to the problem.The design of the algorithm is based on the definition of a rule set, which enable feature extraction and data analysis. The fuzzification process is solved by means of probability density functions. In this way we obtain OWA operators that achieve a high degree of detection in these lesions.The proposed design resolves the problem of false detections by the use of various filters implemented from new rules.},
author = {Aymerich, F. Xavier, Sobrevilla, Pilar, Gili, Jaume, Montseny, Eduard},
journal = {Mathware and Soft Computing},
keywords = {Observación clínica por ordenador; Esclerosis múltiple; Lógica difusa; Inteligencia artificial; Visión artificial; computer vision; fuzzy techniques; magnetic resonance; multiple sclerosis},
language = {eng},
number = {2-3},
pages = {355-363},
title = {Use of fuzzy techniques for detection of multiple sclerosis small lesions.},
url = {http://eudml.org/doc/39159},
volume = {5},
year = {1998},
}

TY - JOUR
AU - Aymerich, F. Xavier
AU - Sobrevilla, Pilar
AU - Gili, Jaume
AU - Montseny, Eduard
TI - Use of fuzzy techniques for detection of multiple sclerosis small lesions.
JO - Mathware and Soft Computing
PY - 1998
VL - 5
IS - 2-3
SP - 355
EP - 363
AB - This work shows an application of algorithms in which fuzzy techniques are used. It is focused on the automation of image analysis for use with a non-invasive technique, as magnetic resonance, in multiple sclerosis patients, and specifically in detection of the smallest lesions. The typical uncertainty in the definition of these lesions lead us to consider that a fuzzy approach is a good solution to the problem.The design of the algorithm is based on the definition of a rule set, which enable feature extraction and data analysis. The fuzzification process is solved by means of probability density functions. In this way we obtain OWA operators that achieve a high degree of detection in these lesions.The proposed design resolves the problem of false detections by the use of various filters implemented from new rules.
LA - eng
KW - Observación clínica por ordenador; Esclerosis múltiple; Lógica difusa; Inteligencia artificial; Visión artificial; computer vision; fuzzy techniques; magnetic resonance; multiple sclerosis
UR - http://eudml.org/doc/39159
ER -