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Challenges of medical image processing

Ingrid Scholl, Til Aach, Thomas M. Deserno, Torsten Kuhlen
Faculty of Electrical Engineering and Information Technology, FH Aachen University of Applied Sciences, Aachen, Germany
Computer Science – Research and Development, Volume 26, Numbers 1-2, 5-13, 2011

@article{scholl2011challenges,

   title={Challenges of medical image processing},

   author={Scholl, I. and Aach, T. and Deserno, T.M. and Kuhlen, T.},

   journal={Computer Science-Research and Development},

   pages={1–9},

   year={2011},

   publisher={Springer}

}

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In todays health care, imaging plays an important role throughout the entire clinical process from diagnostics and treatment planning to surgical procedures and follow up studies. Since most imaging modalities have gone directly digital, with continually increasing resolution, medical image processing has to face the challenges arising from large data volumes. In this paper, we discuss Kilo- to Terabyte challenges regarding (i) medical image management and image data mining, (ii) bioimaging, (iii) virtual reality in medical visualizations and (iv) neuroimaging. Due to the increasing amount of data, image processing and visualization algorithms have to be adjusted. Scalable algorithms and advanced parallelization techniques using graphical processing units have been developed. They are summarized in this paper. While such techniques are coping with the Kilo- to Terabyte challenge, the Petabyte level is already looming on the horizon. For this reason, medical image processing remains a vital field of research.
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