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Proceedings Paper

Image compression for functional imaging
Author(s): Dagan David Feng; Xianjin Li; Wan-Chi Siu
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Paper Abstract

Function imaging has been playing an important role in modern biomedical research and clinical diagnosis, which provides human internal biochemical information previously not available. However, for a routine dynamic study with a typical medical function imaging system, such as positron emission tomography (PET), it is easily to acquire nearly 1000 images for just one patient in one study. Such a large number of images has given a considerable burden for computer image storage space, data processing and transmission time. In this paper, we present the theory and principles for the minimization of image frames in dynamic biomedical function imaging. We show that the minimum number of image frames required is just equal to the model identifiable parameters and that the quality of the physiological parameter estimation, based on these minimum number of image frames, can be controlled at a comparable level. As a result of our study, the image storage space required can be reduced by more than 80 percent.

Paper Details

Date Published: 4 April 1997
PDF: 10 pages
Proc. SPIE 3026, Nonlinear Image Processing VIII, (4 April 1997); doi: 10.1117/12.271134
Show Author Affiliations
Dagan David Feng, Univ. of Sydney (Australia)
Xianjin Li, Univ. of Sydney (Australia)
Wan-Chi Siu, Hong Kong Polytechnic Univ. (Hong Kong)


Published in SPIE Proceedings Vol. 3026:
Nonlinear Image Processing VIII
Edward R. Dougherty; Jaakko T. Astola, Editor(s)

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