Actas de congresos
Automatic method to classify images based on multiscale fractal descriptors and paraconsistent logic
Fecha
2015-01-01Registro en:
3rd International Conference On Mathematical Modeling In Physical Sciences (IC-MSQUARE 2014). Bristol: Iop Publishing Ltd, v. 574, p. 1-4, 2015.
1742-6588
10.1088/1742-6596/574/1/012135
WOS:000352595600135
WOS000352595600135.pdf
2139053814879312
Autor
Universidade Estadual Paulista (Unesp)
Universidade Federal de Uberlândia (UFU)
Faculdade de Medicina de São José do Rio Preto(FAMERP)
Núcleo Transdisciplinar para Estudo do Caos e da Complexidade (NUTECC)
Hospital de Base de São José do Rio Preto
Institución
Resumen
In this study is presented an automatic method to classify images from fractal descriptors as decision rules, such as multiscale fractal dimension and lacunarity. The proposed methodology was divided in three steps: quantification of the regions of interest with fractal dimension and lacunarity, techniques under a multiscale approach; definition of reference patterns, which are the limits of each studied group; and, classification of each group, considering the combination of the reference patterns with signals maximization (an approach commonly considered in paraconsistent logic). The proposed method was used to classify histological prostatic images, aiming the diagnostic of prostate cancer. The accuracy levels were important, overcoming those obtained with Support Vector Machine (SVM) and Bestfirst Decicion Tree (BFTree) classifiers. The proposed approach allows recognize and classify patterns, offering the advantage of giving comprehensive results to the specialists.