Avtor/Urednik		Zagrouba, Ezzeddine; Barhoumi, Walid
Naslov		Semiautomatic detection of tumoral zone
Tip		članek
Vir		Image Anal Stereol
Vol. in št.		Letnik 21, št. 1
Leto izdaje		2002
Obseg		str. 13-8
Jezik		eng
Abstrakt		This paper describes a robust method based on the cooperation of fuzzy classification and regions segmentation algorithms, in order to detect the tumoral zone in the brain Magnetic Resonance Imaging (MRI). On one hand, the classification in fuzzy sets is done by the Fuzzy C-Means algorithm (FCM), where a study of its different parameters and its complexity has been previously realised, which led us to improve it. On the other hand, the segmentation in regions is obtained by an hierarchical method through adaptive thresholding. Then, an operator expert selects a germ in the tumoral zone, and the class containing the sick zone is localised in return for the FCM algorithm. Finally, the superposition of the two partitions of the image will determine the sick zone. The originality of our approach is the parallel exploitation of different types of information in the image by the cooperation of two complementary approaches. This allows us to carry out a pertinent approach for the detection of sick zone in MRI images.
Deskriptorji		MAGNETIC RESONANCE IMAGING FUZZY LOGIC BRAIN NEOPLASMS