Literature DB >> 7565349

A fully automated algorithm for the segmentation of lung fields on digital chest radiographic images.

J Duryea1, J M Boone.   

Abstract

A completely automated algorithm is presented which is capable of identifying both the right- and left-lung fields on digitized chest radiographic images. The algorithm is tested on a sample of 802 chest images against lung fields drawn by a human observer. The average accuracies are found to be 0.957 +/- 0.003 and 0.960 +/- 0.003 for right- and left-lung regions, respectively. To put them into perspective, the results are compared to several other simple segmentation techniques. These include a comparison of two sets of lung fields drawn by the human observer at different times which yielded accuracies of 0.967 +/- 0.005 and 0.967 +/- 0.004 for right- and left-lung regions, respectively.

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Year:  1995        PMID: 7565349     DOI: 10.1118/1.597539

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  7 in total

1.  Lung field segmenting in dual-energy subtraction chest X-ray images.

Authors:  Robert E Alvarez
Journal:  J Digit Imaging       Date:  2004-03       Impact factor: 4.056

2.  Automated lung segmentation in digital chest tomosynthesis.

Authors:  Jiahui Wang; James T Dobbins; Qiang Li
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

3.  Computerized analysis of abnormal asymmetry in digital chest radiographs: evaluation of potential utility.

Authors:  S G Armato; M L Giger; H MacMahon
Journal:  J Digit Imaging       Date:  1999-02       Impact factor: 4.056

4.  A Generic Approach to Lung Field Segmentation From Chest Radiographs Using Deep Space and Shape Learning.

Authors:  Awais Mansoor; Juan J Cerrolaza; Geovanny Perez; Elijah Biggs; Kazunori Okada; Gustavo Nino; Marius George Linguraru
Journal:  IEEE Trans Biomed Eng       Date:  2019-08-14       Impact factor: 4.538

5.  Fully automatic lung segmentation and rib suppression methods to improve nodule detection in chest radiographs.

Authors:  Elaheh Soleymanpour; Hamid Reza Pourreza; Emad Ansaripour; Mehri Sadooghi Yazdi
Journal:  J Med Signals Sens       Date:  2011-07

6.  Segmentation and classification on chest radiography: a systematic survey.

Authors:  Tarun Agrawal; Prakash Choudhary
Journal:  Vis Comput       Date:  2022-01-08       Impact factor: 2.835

7.  A hierarchical method based on active shape models and directed Hough transform for segmentation of noisy biomedical images; application in segmentation of pelvic X-ray images.

Authors:  Rebecca Smith; Kayvan Najarian; Kevin Ward
Journal:  BMC Med Inform Decis Mak       Date:  2009-11-03       Impact factor: 2.796

  7 in total

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