MRI Image Segmentation by K-Means Clustering Method and Detection of Lesions

Azzeddine Riahi

Abstract: Despite the technological advances in the medical field, particularly in medical imaging, the study of the human brain is a difficult topic and remains a topic of strong current research because of a still incomplete understanding of its operation and the availability of computer systems increasingly powerful with the evolution of imaging techniques, high capacity computing machines. . . etc. One of the most used imaging modalities, which is the main subject of this work, is the Magnetic Resonance Imaging (MRI), which has become an indispensable tool for any clinical examination. It has the advantage of being non-invasive and allows the acquisition of two or three-dimensional images in which different contrasts are available. This method also allows the production of brain anatomical studies as well as functional. Through this paper, we present the MRI characteristics which will help in its analysis. But first well discuss a few brain imaging and brain anatomy that will allow us to introduce the different anatomical structures to be localized and identified in the images.

Keywords: Brain imaging, brain MRI, tumor segmentation, Clustering, K-means

How to Cite?: Azzeddine Riahi, "MRI Image Segmentation by K-Means Clustering Method and Detection of Lesions", Volume 4 Issue 6, June 2015, International Journal of Science and Research (IJSR), Pages: 2484-2492, https://www.ijsr.net/getabstract.php?paperid=SUB155690, DOI: https://dx.doi.org/10.21275/SUB155690