Collaborative Compressed I-cloud Medical Image Storage with Decompress Viewer

Abstract

Healthcare collaborative approach is anticipated to be an appropriate solution for disease management structure in the growing global population. Efficient disease management structure needs deep analytical skills in making effective decisions based on medical data. The nature of medical data being huge in size has been categorized as big data. Big data management in a collaborative environment needs multiple technological integrations. In this paper we have proposed an independent cloud based collaborative medical image storage and mobile viewer assisted with effective compression and decompression technique with unique security structure design. The proposed design has considered deep technology exploitation to offer medical image access via mobile devices by considering all the current constraints in terms of storage, image clarity and security. The proposed architecture allows both patient and medical practioners to have a cost effective approach in disease management and treatment process. It also introduces healthcare analysts and practitioners to the advancements in the computing field to effectively handle and make inferences from voluminous and heterogeneous healthcare data. Due to the broad nature of the topic, our primary emphasis will be on introducing healthcare data repositories, challenges, and concepts in data science. Not much focus will be on describing the details of any particular techniques and/or solutions in image compression, security and the medical field in particular other than convenient data access opportunity framework.