Multi Model Clustering Segmentation and Intensive Pragmatic Blossoms (Ipb) Classification Method based Medical Image Retrieval System

Abstract

Nowadays, medical images are generated more and more in their daily activities, which are in millions of sizes. Retrieving medical images from an extensive collection is then a daunting task from a content-based medical image retrieval system (CBMIR) system. Until the extraction of the disease by automated segmentation calculates the bottleneck based on medical image search material. Before that, a few approaches are based on one-to-one image grains that are still sensitive to rotation and expansion. In this work, to address the last problems, introduce Multimodal Clustering Segmentation (MCS)and Intensive Pragmatic Blossoms (IPB) Classification method for medical image retrieval system. Compared to other conventional medical image retrieval, the proposed MCS and IPB method gives a good result. Theoverall retrieval efficiency of the proposed method is 97.23%