New Method of Extraction and Tumor Detection Based on a Histogram Study and Support Vector Machine

Abstract

The location of the tumor, the evaluation of its shape, its position and its interactions with nearby brain structures, etc. are signs and desired indicators. Nowadays clinical tools for in vivo observation areas of the brain such as X-ray scanner, the magnetic resonance imaging (MRI) et., are numerous. Among these techniques, MRI is increasingly used in clinical routine. The image allows precise localization of different structures. However, observation and tumor image analysis prove to be a delicate exercise that requires to use multiple acquisitions under different protocols. In this article we present a new method for detecting and extracting tumor regions applied on brain MRI images. This method consists of three main stages: (i) Extracting the region of interest (the brain) by using the EMBE method. (ii) to study and to make an histogram analysis of the MRI image in order to create learning and initialize the classification algorithm for retrieving and locating the tumor. (iii) Detection and extraction of the tumor, by using by the classification algorithm “Support Vector Machine”. The image will be split into two components which are Tumor class and No-tumor class. Our method will be completed by a characterization of the tumor area to specify its geometric properties. This work will help the radiologists in handling the numerous number of MRI images they have to deal daily. Our contribution will facilitate tumor detection and extraction in a most minimal time.
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