Research Article Open Access

Non Linear Total Variation Based Segmentation of X-Ray Images

Abstract

X-ray Bone image segmentation is an integral component of orthopaedic X-ray image analysis that aims at extracting the bone structure from the muscles and tissues. Automatic segmentation of the bone part in a digital Xray image is a challenging problem because of its low contrast with the surrounding flesh, which itself needs to be discriminated against the background. X ray images are found to have random noise. The random distortion makes it difficult to perform perfect image processing. The non-linear total variation based on partially differential equation algorithm proposed by Leonid et at. [7],is chosen because it effectively removes random noise present and also smoothens the image. The presence of noise and spurious edges further complicates the segmentation. In this paper, we propose an efficient Total-Variation based segmentation technique that integrates several algorithms like non-linear total variation algorithm to remove random noise present, edge detection, Otsu’s global thresholding and application of morphological operators. Experiments on several X-ray images taken from IRMA Database for different parts of the body like hand, abdomen and spine images provide encouraging results.

Prachi.Bhende,Prof.A.N.Cheeran

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