A novel approach to medical image compression.
As medical/biological imaging facilities move towards complete film-less imaging, compression plays a key role. Although lossy compression techniques yield high compression rates, the medical community has been reluctant to adopt these methods, largely for legal reasons, and has instead relied on lossless compression techniques that yield low compression rates. The true goal is to maximise compression while maintaining clinical relevance and balancing legal risk. This paper proposes a novel model-based compression technique that makes use of clinically relevant regions as defined by radiologists. Lossless compression is used in these clinically relevant regions, and lossy compression is used everywhere else.
Department of Mathematics and Computer Science, Wilkes University, Wilkes-Barre, PA 18766, USA. zukoski@wilkes.edu
Matthew J
MJ
Zukoski
Terrance
T
Boult
Tunç
T
Iyriboz
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D016248:Computer Storage Devices; D044962:Data Compression; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D013902:Radiography, Thoracic / Q000379:methods; D011871:Radiology / Q000379:methods; D011873:Radiology Information Systems; D012815:Signal Processing, Computer-Assisted; D012984:Software; D014965:X-Rays