Main Article Content

Abstract

Image processing have a vast area under research, in which Medical Imaging is the most significant area to work in. Basically Medical Imaging can be explained as the process of creating human body images for medical and research work. For tumor detection various techniques such as MRI (Magnetic Resonance Imaging), CT (Computerised tomography) scan and Microwave are available among mentioned techniques MRI delivers the best images as it has higher resolution. The abnormalities of the bone can be identified easily by MRI imaging. Because, the MRI images are of low contrast and contain speckle noise. The image quality may not be good for analyzing. So, to reduce speckle noise and for better analyzing, preprocessing can be done using gabor filter. To increase the contrast of the image using adaptive histogram equalization .Then segmentation method is used to segment the tumor part of bone using k-Means algorithm. Feature extraction can be used to extract and speed up the decision-making process for SVM. Finally, the output is displayed in SVM and this helps to increase the accuracy of an abnormalities. In this paper the tumor detection have been proposed using machine learning

Article Details

How to Cite
Vanitha K, Jeeva S, Nandhine K T, Nihal M A, & , Monisha K. (2019). Analysis and detection of bone tumor in MRI images using machine learning . International Journal of Intellectual Advancements and Research in Engineering Computations, 7(2), 2918–2924. Retrieved from https://ijiarec.com/ijiarec/article/view/1150