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Segmentation of suspicious clustered microcalcifications in mammograms.

Publication ,  Journal Article
Gavrielides, MA; Lo, JY; Vargas-Voracek, R; Floyd, CE
Published in: Med Phys
January 2000

We have developed a multistage computer-aided diagnosis (CAD) scheme for the automated segmentation of suspicious microcalcification clusters in digital mammograms. The scheme consisted of three main processing steps. First, the breast region was segmented and its high-frequency content was enhanced using unsharp masking. In the second step, individual microcalcifications were segmented using local histogram analysis on overlapping subimages. For this step, eight histogram features were extracted for each subimage and were used as input to a fuzzy rule-based classifier that identified subimages containing microcalcifications and assigned the appropriate thresholds to segment any microcalcifications within them. The final step clustered the segmented microcalcifications and extracted the following features for each cluster: the number of microcalcifications, the average distance between microcalcifications, and the average number of times pixels in the cluster were segmented in the second step. Fuzzy logic rules incorporating the cluster features were designed to remove nonsuspicious clusters, defined as those with typically benign characteristics. A database of 98 images, with 48 images containing one or more microcalcification clusters, provided training and testing sets to optimize the parameters and evaluate the CAD scheme, respectively. The results showed a true positive rate of 93.2% and an average of 0.73 false positive clusters per image. A comparison of our results with other reported segmentation results on the same database showed comparable sensitivity and at the same time an improved false positive rate. The performance of the CAD scheme is encouraging for its use as an automatic tool for efficient and accurate diagnosis of breast cancer.

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Published In

Med Phys

DOI

ISSN

0094-2405

Publication Date

January 2000

Volume

27

Issue

1

Start / End Page

13 / 22

Location

United States

Related Subject Headings

  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Humans
  • Fuzzy Logic
  • Female
  • False Positive Reactions
  • Evaluation Studies as Topic
  • Databases, Factual
 

Citation

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Gavrielides, M. A., Lo, J. Y., Vargas-Voracek, R., & Floyd, C. E. (2000). Segmentation of suspicious clustered microcalcifications in mammograms. Med Phys, 27(1), 13–22. https://doi.org/10.1118/1.598852
Gavrielides, M. A., J. Y. Lo, R. Vargas-Voracek, and C. E. Floyd. “Segmentation of suspicious clustered microcalcifications in mammograms.Med Phys 27, no. 1 (January 2000): 13–22. https://doi.org/10.1118/1.598852.
Gavrielides MA, Lo JY, Vargas-Voracek R, Floyd CE. Segmentation of suspicious clustered microcalcifications in mammograms. Med Phys. 2000 Jan;27(1):13–22.
Gavrielides, M. A., et al. “Segmentation of suspicious clustered microcalcifications in mammograms.Med Phys, vol. 27, no. 1, Jan. 2000, pp. 13–22. Pubmed, doi:10.1118/1.598852.
Gavrielides MA, Lo JY, Vargas-Voracek R, Floyd CE. Segmentation of suspicious clustered microcalcifications in mammograms. Med Phys. 2000 Jan;27(1):13–22.

Published In

Med Phys

DOI

ISSN

0094-2405

Publication Date

January 2000

Volume

27

Issue

1

Start / End Page

13 / 22

Location

United States

Related Subject Headings

  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Humans
  • Fuzzy Logic
  • Female
  • False Positive Reactions
  • Evaluation Studies as Topic
  • Databases, Factual