Literature DB >> 9165420

A computerized analysis system in chest radiography: evaluation of interstitial lung abnormalities.

S Kido1, J Ikezoe, S Tamura, H Nakamura, C Kuroda.   

Abstract

We evaluated the usefulness of a computerized analysis system in the detection of interstitial lung abnormalities in digitized chest radiography. This system uses the processes of four-directional Laplacian-Gaussian filtering, linear opacity judgment, and linear opacity subtraction. For qualitative analysis, we employed a combined radiographic index, which was calculated from two normalized radiographic indices obtained by linear opacity judgment and subtraction of linear opacities. We selected 50 regions of interest (ROIs) in patients with mild interstitial lung abnormalities, 50 ROIs in patients with severe interstitial lung abnormalities, and 50 ROIs in individuals with normal lung parenchyma. High-resolution computed radiography (HRCT) findings were used as the standard of reference for this study. These ROIs were processed by our computerized analysis system, and radiographic indices were obtained from each ROI. The area under the receiver operating characteristic curve (Az) was used as the measure of performance. The combined radiographic index provided better results in the mild interstitial lung abnormality group (Az = 0.94 +/- 0.02), but it also yielded good results in the severe interstitial lung abnormality group (Az = 0.98 +/- 0.01). These results indicate that this system of combining radiographic indices has improved the detection performance over that with our previous system.

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Year:  1997        PMID: 9165420      PMCID: PMC3453003          DOI: 10.1007/bf03168557

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


  13 in total

1.  Image feature analysis and computer-aided diagnosis in digital radiography: classification of normal and abnormal lungs with interstitial disease in chest images.

Authors:  S Katsuragawa; K Doi; H MacMahon
Journal:  Med Phys       Date:  1989 Jan-Feb       Impact factor: 4.071

Review 2.  ROC methodology in radiologic imaging.

Authors:  C E Metz
Journal:  Invest Radiol       Date:  1986-09       Impact factor: 6.016

Review 3.  Pattern recognition in diffuse lung disease. A review of theory and practice.

Authors:  G P Genereux
Journal:  Med Radiogr Photogr       Date:  1985-06

4.  Some practical issues of experimental design and data analysis in radiological ROC studies.

Authors:  C E Metz
Journal:  Invest Radiol       Date:  1989-03       Impact factor: 6.016

5.  Diagnostic radiology: usage and trends in the United States, 1964-1980.

Authors:  F A Mettler
Journal:  Radiology       Date:  1987-01       Impact factor: 11.105

6.  Theory of edge detection.

Authors:  D Marr; E Hildreth
Journal:  Proc R Soc Lond B Biol Sci       Date:  1980-02-29

7.  An image analyzing system for interstitial lung abnormalities in chest radiography. Detection and classification by Laplacian-Gaussian filtering and linear opacity judgment.

Authors:  S Kido; J Ikezoe; H Naito; M Masuike; S Tamura; T Kozuka
Journal:  Invest Radiol       Date:  1994-02       Impact factor: 6.016

8.  The meaning and use of the area under a receiver operating characteristic (ROC) curve.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1982-04       Impact factor: 11.105

9.  ROC analysis applied to the evaluation of medical imaging techniques.

Authors:  J A Swets
Journal:  Invest Radiol       Date:  1979 Mar-Apr       Impact factor: 6.016

10.  Image feature analysis and computer-aided diagnosis in digital radiography: detection and characterization of interstitial lung disease in digital chest radiographs.

Authors:  S Katsuragawa; K Doi; H MacMahon
Journal:  Med Phys       Date:  1988 May-Jun       Impact factor: 4.071

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