IoT based leukemia detection using Fuzzy C-means clustering Technique

Abstract

In children and adults, acute lymphoblastic leukemia (ALL) is the most severe blood disease, affecting both simultaneously and in equal proportion. Microscopy image processing software is used to perform image processing steps on microscopic images, such as improving the quality of images, segmenting images, and extracting features from them. In order to perform image processing steps on microscopic images, image processing software must be used. In addition to being a quick and inexpensive method of detecting pathogens, image-based detection does not necessitate the purchase of expensive laboratory equipment. The mathematical programming language has developed an easy-to-use tool for identifying and segmenting white blood cells. This feature makes user interaction with the white blood cell detection and segmentation program easier. The FCM (Fuzzy C-Means clustering) algorithm has been used to detect and extract blood cell features from images.