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Proceedings Paper

Improved automatic adjustment of density and contrast in FCR system using neural network
Author(s): Hideya Takeo; Nobuyoshi Nakajima; Masamitsu Ishida; Hisatoyo Kato
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Paper Abstract

FCR system has an automatic adjustment of image density and contrast by analyzing the histogram of image data in the radiation field. Advanced image recognition methods proposed in this paper can improve the automatic adjustment performance, in which neural network technology is used. There are two methods. Both methods are basically used 3-layer neural network with back propagation. The image data are directly input to the input-layer in one method and the histogram data is input in the other method. The former is effective to the imaging menu such as shoulder joint in which the position of interest region occupied on the histogram changes by difference of positioning and the latter is effective to the imaging menu such as chest-pediatrics in which the histogram shape changes by difference of positioning. We experimentally confirm the validity of these methods (about the automatic adjustment performance) as compared with the conventional histogram analysis methods.

Paper Details

Date Published: 1 May 1994
PDF: 12 pages
Proc. SPIE 2163, Medical Imaging 1994: Physics of Medical Imaging, (1 May 1994); doi: 10.1117/12.174245
Show Author Affiliations
Hideya Takeo, Fuji Photo Film Co., Ltd. (Japan)
Nobuyoshi Nakajima, Fuji Photo Film Co., Ltd. (Japan)
Masamitsu Ishida, Fuji Photo Film Co., Ltd. (Japan)
Hisatoyo Kato, Fuji Photo Film Co., Ltd. (Japan)


Published in SPIE Proceedings Vol. 2163:
Medical Imaging 1994: Physics of Medical Imaging
Rodney Shaw, Editor(s)

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