MIDOM—A DICOM-Based Medical Image Communication System

Despite the existing medical infrastructure being limited in terms of interoperability, amount multimedia transferred over network and shared through various channels increases rapidly. In search consultations with colleagues, professionals consent their patients, usually exchange multimedia, mainly form images, by using standard instant messaging services which utilize lossy compression algorithms. That consultation paradigm can easily lead to losses image representation that be misinterpreted wrong diagnosis. This paper presents MIDOM—Medical Imaging Diagnostics on Move, a DICOM-based communication system enhanced couple variants our previously developed custom lossless Classification Blending Predictor Coder (CBPC) method. The generally exploits idea end devices used general population alike are satisfactorily performant energy-efficient, up point support complex methods successfully. has been implemented appropriately integrated Orthanc, lightweight DICOM server, images storing PACS server. We benchmarked thoroughly five real-world anonymized sets ratios latency reduction, aiming simulate scenarios availability might hardly reachable or other ways limited. results clearly show question pays off nearly every testing scenario lowering at least 60% required send raw uncompressed 25% best-case, while maintaining perfect reconstruction and, thus, providing more suitable environment for healthcare applications.