Literature DB >> 16752044

Study of automatic enhancement for chest radiograph.

Chen Shuyue1, Hou Honghua, Zeng Yanjun, Xu Xiaomin.   

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.

Entities:  

Mesh:

Year:  2006        PMID: 16752044      PMCID: PMC3045154          DOI: 10.1007/s10278-006-0623-7

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  6 in total

1.  Adaptive local contrast enhancement method for medical images displayed on a video monitor.

Authors:  T H Lin; T Kao
Journal:  Med Eng Phys       Date:  2000-03       Impact factor: 2.242

2.  Computerized detection of pulmonary nodules in chest radiographs based on morphological features and wavelet snake model.

Authors:  Bilgin Keserci; Hiroyuki Yoshida
Journal:  Med Image Anal       Date:  2002-12       Impact factor: 8.545

3.  Regionally adaptive histogram equalization of the chest.

Authors:  R H Sherrier; G A Johnson
Journal:  IEEE Trans Med Imaging       Date:  1987       Impact factor: 10.048

4.  Adaptive image contrast enhancement using generalizations of histogram equalization.

Authors:  J A Stark
Journal:  IEEE Trans Image Process       Date:  2000       Impact factor: 10.856

5.  Image enhancement via adaptive unsharp masking.

Authors:  A Polesel; G Ramponi; V J Mathews
Journal:  IEEE Trans Image Process       Date:  2000       Impact factor: 10.856

6.  Design and testing of artifact-suppressed adaptive histogram equalization: a contrast-enhancement technique for display of digital chest radiographs.

Authors:  K Rehm; G W Seeley; W J Dallas; T W Ovitt; J F Seeger
Journal:  J Thorac Imaging       Date:  1990-01       Impact factor: 3.000

  6 in total
  3 in total

1.  Automatic screening for tuberculosis in chest radiographs: a survey.

Authors:  Stefan Jaeger; Alexandros Karargyris; Sema Candemir; Jenifer Siegelman; Les Folio; Sameer Antani; George Thoma
Journal:  Quant Imaging Med Surg       Date:  2013-04

2.  Multi-scale Morphological Image Enhancement of Chest Radiographs by a Hybrid Scheme.

Authors:  Fatemeh Shahsavari Alavijeh; Homayoun Mahdavi-Nasab
Journal:  J Med Signals Sens       Date:  2015 Jan-Mar

3.  Artificial intelligence-aided diagnosis model for acute respiratory distress syndrome combining clinical data and chest radiographs.

Authors:  Kai-Chih Pai; Wen-Cheng Chao; Yu-Len Huang; Ruey-Kai Sheu; Lun-Chi Chen; Min-Shian Wang; Shau-Hung Lin; Yu-Yi Yu; Chieh-Liang Wu; Ming-Cheng Chan
Journal:  Digit Health       Date:  2022-08-15
  3 in total

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