Medical image blob detection with feature stability and KNN classification

Object detection methods with feature stability along with the use of KNN algorithm are proposed within this paper. A scale-space tree is constructed based on the blobs that were created from a series of images after blurring. Features and spatial information provides the role in scalespace tree construction. After the process of blob extraction, users determine the type of blobs that were detected within the image by distinguishing classes to create ground truth images. Within the same process, KNN algorithm is applied to distinguish classes of the image´s blob to demonstrate its performance.