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Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques.

Publication ,  Journal Article
Yin, FF; Giger, ML; Doi, K; Vyborny, CJ; Schmidt, RA
Published in: J Digit Imaging
February 1994

Mammographic screening of asymptomatic women has shown effectiveness in the reduction of breast cancer mortality. We are developing a computerized scheme for the detection of mammographic masses as an aid to radiologists in mammographic screening programs. Possible masses on digitized screen/film mammograms are initially identified using a nonlinear bilateral-subtraction technique, which is based on asymmetric density patterns occurring in corresponding portions of right and left mammograms. In this study, we analyze the characteristics of actual masses and nonmass detections to develop feature-analysis techniques with which to reduce the number of nonmass (ie, false-positive) detections. These feature-analysis techniques involve (1) the extraction of various features (such as area, contrast, circularity and border-distance based on the density and geometric information of masses in both processed, and original breast images), and (2) tests of the extracted features to reduce nonmass detections. Cumulative histograms of both actual-mass detections and nonmass detections are used to characterize extracted features and to determine the cutoff values used in the feature tests. The effectiveness of the feature-analysis techniques is evaluated in combination with the computerized detection scheme that uses the nonlinear bilateral-subtraction technique using free-response receiver operating characteristic analysis and 77 patient cases (308 mammograms). Results show that the feature-analysis techniques effectively improve the performance of the computerized detection scheme: about 35% false-positive detections were eliminated without loss in sensitivity when the feature-analysis techniques were used.

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Published In

J Digit Imaging

DOI

ISSN

0897-1889

Publication Date

February 1994

Volume

7

Issue

1

Start / End Page

18 / 26

Location

United States

Related Subject Headings

  • Radiographic Image Enhancement
  • ROC Curve
  • Nuclear Medicine & Medical Imaging
  • Mass Screening
  • Mammography
  • Image Interpretation, Computer-Assisted
  • Humans
  • Female
  • False Positive Reactions
  • Breast Neoplasms
 

Citation

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Yin, F. F., Giger, M. L., Doi, K., Vyborny, C. J., & Schmidt, R. A. (1994). Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques. J Digit Imaging, 7(1), 18–26. https://doi.org/10.1007/BF03168475
Yin, F. F., M. L. Giger, K. Doi, C. J. Vyborny, and R. A. Schmidt. “Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques.J Digit Imaging 7, no. 1 (February 1994): 18–26. https://doi.org/10.1007/BF03168475.
Yin FF, Giger ML, Doi K, Vyborny CJ, Schmidt RA. Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques. J Digit Imaging. 1994 Feb;7(1):18–26.
Yin, F. F., et al. “Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques.J Digit Imaging, vol. 7, no. 1, Feb. 1994, pp. 18–26. Pubmed, doi:10.1007/BF03168475.
Yin FF, Giger ML, Doi K, Vyborny CJ, Schmidt RA. Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques. J Digit Imaging. 1994 Feb;7(1):18–26.
Journal cover image

Published In

J Digit Imaging

DOI

ISSN

0897-1889

Publication Date

February 1994

Volume

7

Issue

1

Start / End Page

18 / 26

Location

United States

Related Subject Headings

  • Radiographic Image Enhancement
  • ROC Curve
  • Nuclear Medicine & Medical Imaging
  • Mass Screening
  • Mammography
  • Image Interpretation, Computer-Assisted
  • Humans
  • Female
  • False Positive Reactions
  • Breast Neoplasms