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1 May 1994 Improved automatic adjustment of density and contrast in FCR system using neural network
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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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hideya Takeo, Nobuyoshi Nakajima, Masamitsu Ishida, and Hisatoyo Kato "Improved automatic adjustment of density and contrast in FCR system using neural network", Proc. SPIE 2163, Medical Imaging 1994: Physics of Medical Imaging, (1 May 1994); https://doi.org/10.1117/12.174245
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