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Author:

Chen, Shuyue (Chen, Shuyue.) | Hou, Honghua (Hou, Honghua.) | Zeng, Yanjun (Zeng, Yanjun.) | Xu, Xiaomin (Xu, Xiaomin.)

Indexed by:

EI Scopus SCIE

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.

Keyword:

medical image processing image enhancement SARS chest radiograph

Author Community:

  • [ 1 ] Beijing Univ Technol, Biomech & Med Informat Inst, Beijing 100022, Peoples R China
  • [ 2 ] N Univ China, State Educ Minist Instrumentat Sci & Dynam Measur, Key Lab, Taiyuan 030051, Peoples R China
  • [ 3 ] Beijing Univ Technol, Ctr Biomed Engn, Beijing 100022, Peoples R China
  • [ 4 ] Children Hosp Shanxi Prov, Taiyuan 030013, Peoples R China

Reprint Author's Address:

  • [Zeng, Yanjun]Beijing Univ Technol, Biomech & Med Informat Inst, Beijing 100022, Peoples R China

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Source :

JOURNAL OF DIGITAL IMAGING

ISSN: 0897-1889

Year: 2006

Issue: 4

Volume: 19

Page: 371-375

4 . 4 0 0

JCR@2022

ESI Discipline: CLINICAL MEDICINE;

JCR Journal Grade:3

Cited Count:

WoS CC Cited Count: 13

SCOPUS Cited Count: 18

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 12

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