Resumen

VIANNEY-KINANI, JEAN MARIE; ROSALES-SILVA, ALBERTO J.; GALLEGOS-FUNES, FRANCISCO J.  y  ARELLANO, ALFONSO. COMPUTER-AIDED DIAGNOSIS OF BRAIN TUMORS USING IMAGE ENHANCEMENT AND FUZZY LOGIC. Dyna rev.fac.nac.minas [online]. 2014, vol.81, n.183, pp.148-157. ISSN 0012-7353.  https://doi.org/10.15446/dyna.v81n183.36838.

A robust medical image processing system depends upon a variety of aspects, including a proper image enhancement, and an optimal segmentation. An algorithm was proposed in this paper to facilitate the implementation of these two steps. First a Magnetic Resonance (MR) image is enhanced via spatial domain filtering and its contrast is improved, next, the image is segmented using fuzzy C-mean clustering, then the region of interest which might be the tumor or edema, is detected and delineated. The key advantage of this image processing pipeline is the simultaneous use of features computed from the intensity properties of the image in a cascading pattern which makes the computation self-contained. Performance evaluation of the proposed algorithm was carried out on brain images from different MRI's and the algorithm proved to be successful, comparing it with other dedicated applications.

Palabras clave : MRI; Region of interest; Segmentation; Clustering; IRM (Imagen de Resonancia Magnética); Región de interés; Segmentación; Algoritmo de agrupamiento.

        · resumen en Inglés     · texto en Inglés     · Inglés ( pdf )