Distributed Storage and Processing of Image Data

Abstract: Systems operating in a medical environment need to maintain high standards regarding availability and performance. Large amounts of images are stored and studied to determine what is wrong with a patient. This puts hard requirements on the storage of the images. In this thesis, ways of incorporating distributed storage into a medical system are explored. Products, inspired by the success of Google, Amazon and others, are experimented with and compared to the current storage solutions. Several “non-relational databases” (NoSQL) are investigated for storing medically relevant metadata of images, while a set of distributed file systems are considered for storing the actual images. Distributed processing of the stored data is investigated by using Hadoop MapReduce to generate a useful model of the images' metadata.