Design and Development of Enhanced Compression Model for Content Representation of Radiological Imaging

Abstract

newline Content representation of an image is an active region of experimentation with emerging use cases such as satellite communication, hurdle detection, pattern recognition, telemedicine, and healthcare information. The aim of Content representation is a depiction of an image with fewer amounts of coefficients than an actual image without compromising the quality of the image. It is the pre-stage in image compression. Image compression intends to diminish image inconsistency and store or transfer the data more efficiently and effectively. Medical data, which comprises clinical information, images, and other sensory information, is becoming a crucial part of the care of the patient even during the illness diagnostic process. Telemedicine essentially refers to quotMedicine at a Distance,quot which is accomplished by sending an electronic patient record to a distant medical Centre for diagnosis, allowing doctors/specialists in different geographical regions to consult and learn about the health condition of their crucial patients. Because a radiological image is enormous, in its raw state, it necessitates a lot of disk space, and transmission demands a lot of bandwidth, transmission time, and expense. Medical data must therefore be compressed before transmission or storage. To do so, a new representation technique for elevated radiological image transmission while ensuring diagnostic integrity is required. newlineThe motive of this thesis is to develop an innovative visualization technique and improved quality framework for an impactful lossless compression procedure of high-speed transmission of medical images while sustaining diagnostic integrity and not lowering image quality to an unacceptable level. Several general-purpose compression techniques have been developed. Many approaches have been proposed to effectively compress radiological images and challenges.