Multispectral images segmentation for biomedical applications diagnosis: K-means oriented approach
Abdellatif Bouzid-Daho, Mohamed Boughazi, Benaoumeur Senouci · 2017
The segmentation of multispectral images is considered as a key step in image processing for biomedical applications. Performing this step using the appropriate methodology is a real issue that being investigated by the research community. In this paper, we propose a new algorithm to perform automatic segmentation based on k-means methodology within an automatic generation of the optimal value of “K”. We applied the new algorithm on a dataset of a real medical image. The obtained experimental results showed the efficiency and the speed of our methodology on the choice of the “K” value, and to track pathology's evolution by the detection of cancerous blood cells for biomedical diagnostic, and some segmentation experiments show that our proposed system has better accuracy almost than some other methods.