CBMIR: Content Based Medical Image Retrieval Using Hybrid Texture Feature Extraction Method

Abstract

Due to the revolution of digital era in the medical domain at various hospitals across the world, the online users on the internet access have been increased. So the amount of collections of digitized medical images has grown rapidly and continuously. As well it is ratting significant to mention that the images are globally used by radiologists, professors in medical colleges and Lab technicians, etc. These Images are increasingly applied to communicate information about patient history. In this context, there is a necessity to develop appropriate systems to manage these medical images in storage and retrieval for diagnosis of the patient information. Another big issue is the convolution of image data and that can be interpreted in different ways. In order to manipulate these data and establish policies to its content is very tedious job. This will raise another big question. These issues motivated the researchers to give more focus on the image retrieval area whose goal is trying to solve those problems to provide an efficient retrieval system to the user community. In this perspective, this work has been proposed to facilitate radiologists, professors in medical colleges, lab technicians, and all other medical image user communities for their purpose for easy access from the remote location.