Computed Quality Assessment of MPEG4-compressed DICOM Video Data.
Digital Imaging and Communication in Medicine (DICOM) has become one of the most popular standards in medicine. This standard specifies the exact procedures in which digital images are exchanged between devices, either using a network or storage medium. Sources for images vary; therefore there exist definitions for the exchange for CR, CT, NMR, angiography, sonography and so on. With its spreading, with the increasing amount of sources included, data volume is increasing, too. This affects storage and traffic. While for long-time storage data compression is generally not accepted at the moment, there are many situations where data compression is possible: Telemedicine for educational purposes (e.g. students at home using low speed internet connections), presentations with standard-resolution video projectors, or even the supply on wards combined receiving written findings. DICOM comprises compression: for still image there is JPEG, for video MPEG-2 is adopted. Within the last years MPEG-2 has been evolved to MPEG-4, which squeezes data even better, but the risk of significant errors increases, too. Within the last years effects of compression have been analyzed for entertainment movies, but these are not comparable to videos of physical examinations (e.g. echocardiography). In medical videos an individual image plays a more important role. Erroneous single images affect total quality even more. Additionally, the effect of compression can not be generalized from one test series to all videos. The result depends strongly on the source. Some investigations have been presented, where different MPEG-4 algorithms compressed videos have been compared and rated manually. But they describe only the results in an elected testbed. In this paper some methods derived from video rating are presented and discussed for an automatically created quality control for the compression of medical videos, primary stored in DICOM containers.
Frankewitsch
Thomas
T
Department of Medical Informatics, University of Erlangen-Nuernberg, Germany.
Söhnlein
Sven
S
Müller
Marcel
M
Prokosch
Hans-Ulrich
HU
D000465:Algorithms; D044962:Data Compression; D004452:Echocardiography; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D017216:Telemedicine