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Study of automatic enhancement for chest radiograph.

作者信息

Shuyue Chen, Honghua Hou, Yanjun Zeng, Xiaomin Xu

机构信息

The Key Laboratory of the State Education Ministry on Instrumentation Science and Dynamic Measurement, North University of China, Taiyuan, 030051, People's Republic of China.

出版信息

J Digit Imaging. 2006 Dec;19(4):371-5. doi: 10.1007/s10278-006-0623-7.

Abstract

Because of the large difference of the densities in the lung and other structures, the chest x-ray image behaves as a wide-range intensity distribution, which brings on a bit of difficulty to investigate the focus. In the paper, according to the intensity properties of the chest radiograph, the chest radiographic image is divided into three subregions, and a piecewise linear transformation model is established. An approach of automatic enhancement is presented, based on the gray-level normalization. The average enhanced ratios of three subregions of the normal and severe acute respiratory syndrome image are increased by 10.70% and 25.55%, respectively. The technique is proved to be effective through the evaluation of the improved images.

摘要

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