Study of automatic enhancement for chest radiograph
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 ches...
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Veröffentlicht in: | Journal of digital imaging 2006-12, Vol.19 (4), p.371-375 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 0897-1889 1618-727X |
DOI: | 10.1007/s10278-006-0623-7 |