Staff Members - Benha University
Automated Cell Nuclei Segmentation for Breast Fine Needle Aspiration Cytology
Signal Processing • 2012
Publication Information
Authors
Yasmeen M George, Bassant M Bagoury, Hala H Zayed, Mohamed I Roushdy
Keywords
Not Available
Journal
Signal Processing
Publisher
Elsevier
Volume
Not Available
Issue
Not Available
Pages
Not Available
publication.type
International
Paper Link
Not Available
Supplementary Materials
Not Available
Abstract
Breast cancer detection and segmentation of cytological images is the standard clinical
practice for the diagnosis and prognosis of breast cancer. This paper presents a fully
automated method for cell nuclei detection and segmentation in breast cytological images.
The images are enhanced with histogram stretching and contrast-limited adaptive histogram
equalization (CLAHE). The locations of the cell nuclei in the image are detected with circular
Hough transform (CHT) and local maximum filtering. The elimination of false positive
practice for the diagnosis and prognosis of breast cancer. This paper presents a fully
automated method for cell nuclei detection and segmentation in breast cytological images.
The images are enhanced with histogram stretching and contrast-limited adaptive histogram
equalization (CLAHE). The locations of the cell nuclei in the image are detected with circular
Hough transform (CHT) and local maximum filtering. The elimination of false positive