Bone Cancer Detection Using K-Means Segmentation and Knn Classification

Abstract

From couple of years image processing techniques are extensively utilized for different therapeutic image modalities in which to distinguish infection as in brief period time factor assumes an extremely critical job. The most ideal approach to depict bone malignancy in all stages utilizing image processing. Identifying cancer in the bone is a testing issue because of its complex structure. Here, past analysts have given far reaching survey of bone malignant growth recognition using image processing strategies. A decent research work has been made to the CAD framework behind distinguishing proof of bone malignant growth by images. In this paper we proposed a bone malignant growth identification utilizing k-means segmentation and KNN classifier to recognize the bone disease utilizing image processing strategy for ultra sound images of bones. The proposed outcomes are promising with more exactness up to 98.14% accuracy.