Detecting Microcalcifications in Digital Mammograms Using Wavelet Domain Hidden Markov Tree Model

Authors

Emma Regentova, University of Nevada, Las VegasFollow
Lei Zhang, University of Nevada, Las VegasFollow
Jun Zheng, University of Nevada, Las VegasFollow
G. Veni, University of Nevada, Las VegasFollow

Document Type

Conference Proceeding

Publication Date

8-30-2006

Publication Title

28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06

Publisher

Institute of Electrical and Electronics Engineers

First page number:

1972

Last page number:

1975

Abstract

In this paper we investigate the performance of statistical modeling of digital mammograms by means of wavelet domain hidden Markov tree model (WHMT) for its inclusion to a computer-aided diagnostic prompting system for detecting microcalcification (MC) clusters. The system incorporates: (1) gross-segmentation of mammograms for obtaining the breast region; (2) eliminating the pepper-type noise, (3) block-wise wavelet transform of the breast signal and likelihood calculation; (4) image segmentation; (5) postprocessing for retaining MC clusters. FROC curves are obtained for all MC clusters containing mammograms of mini-MIAS database. 100% of true positive cases are detected by the system at 2.9 false positives per case.

Keywords

Breast cancer; Cities and towns; Hidden Markov models; Image databases; Image segmentation; Tree graphs; USA Councils; Wavelet coefficients; Wavelet domain; Wavelet transforms

Disciplines

Bioimaging and Biomedical Optics | Biomechanics and Biotransport | Biomedical Devices and Instrumentation | Biomedical Engineering and Bioengineering | Diagnosis | Electrical and Computer Engineering | Electromagnetics and Photonics | Medicine and Health Sciences | Molecular, Cellular, and Tissue Engineering | Surgical Procedures, Operative

Language

English

Comments

Conference held: New York, NY, Aug. 30 2006-Sept. 3 2006

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.

Repository Citation

Regentova, E., Zhang, L., Zheng, J., Veni, G. (2006). Detecting Microcalcifications in Digital Mammograms Using Wavelet Domain Hidden Markov Tree Model. 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 1972-1975. Institute of Electrical and Electronics Engineers.