Study of automatic enhancement for chest radiograph

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.

MeSH terms

  • Humans
  • Image Processing, Computer-Assisted*
  • Radiographic Image Enhancement / methods*
  • Radiography, Thoracic / methods*