Comparative Evaluation of Segmentation Algorithms for Tumor Cells Detection from Bone MR Scan Imagery

Abstract

Bone cancer is considered to be the most dangerous and often the cause of early death around the globe. Therefore, early detection of the bone cancer has become needed to cure the patient. A number of segmentation methods have been used for bone tumor detection. This study gives a comparative assessment of the existing bone cancer segmentation methods and also proposed an object labeling algorithm for the segmentation of bone tumor from magnetic resonance images (MRI). The comparison of the existing bone tumor segmentation algorithms with the proposed one has been done on the basis of quantitative methods like the dice similarity coefficient (DSC) and the structural similarity index measurement (SSIM). The comparative evaluation found that the object labeling algorithm provides the highest mean of DSC 96.04% and mean of SSIM 98.33% over the other segmentation methods.