Investigation of Medical Image Segmentation Using Machine Learning Based Fuzzy Reliability Function for MIoT

Abstract

Nowadays the image segmentation is placed a crucial role in the medical image analysis process. The automatic image segmentation process using Medical Internet of Things (MIoT) is applied to the image for analyzing the various directions such as horizontal and vertical to identify the abnormal growth of the cells present in the human part. In the recent past less accurate, more noise, high error rate and false segmentation, lead to reduce the entire disease identification process. In this research work, automatic image segmentation process using multimodal machine learning based segmentation with fuzzy reliability function techniques used to minimize the false segmentation rate and increase the recognition accuracy. This research presenting the medical imaging of the brain and retina has been segmented for clinical experimental analysis by applying the various unsupervised clustering technique and edge detection techniques to improve efficiency of the system in MIoT environment.