A Survey on Deep Learning Aided Telepathology and its Methodologies

Dynamics in Telepathology has been an emerging field since 1986. Recent Researches on Telepathology have concentrated much on Digital Pathology and Computer-Aided Pathology with an emerging power of computations like Edge Computing Technologies and so on., which can even facilitate live microscopic sessions to a remote place. Although such platforms allows a pathological consultant or pathologists team to retrieve, manage and process a real or surpassed microscopic image simultaneously, deployed in a remotely located web servers or any handheld devices, these systems still lag in Image Processing with specific Applications and also Speeding up of image Transmission Time and less interest on Cyber Human Systems. Most importantly the system shows less focus on the security of patient's Data. In today's computer world, integrated systems with increasingly complex and functional software tools are being developed and are becoming co-partners in the pathology diagnostic toolbox on the road to personalized medicine. Recent studies have described various barriers that can spread worldwide by validating telemedicine technology for diagnostic purposes. Surgical remote pathology is of paramount importance in covering its entire range. These technical tools undoubtedly facilitate digital pathology and computational pathology, opening up new approaches to the study of the calculation of individual diseased tissues, and the practice of pathology in distant tissues. Transform rural areas without pathologists for free. Due to technical factors, impressions on workflow, and information technology infrastructure implementation of Digital Pathology is still challenging for pathologists which must have to be considered. Still, the implementation of Telepathology is inefficient in developing countries due to the lack of IT Infra Structure and accessibility.