Automated segmentation of digitized mammograms.
OBJECTIVE
Fast and reliable segmentation of digital mammograms into breast and nonbreast regions is an important prerequisite for further image analysis. We are developing a segmentation algorithm that is fully automated and can operate independent of type of digitizing system, image orientation, and image projection.


METHODS
The algorithm identifies unexposed and direct-exposure image regions and generates a border surrounding the valid breast region, which can then be used as input for further image analysis. The program was tested on 740 digitized mammograms; the segmentation results were evaluated by two expert mammographers and two medical physicists.


RESULTS
In 97% of the mammograms, the segmentation results were rated as acceptable for use in computer-aided diagnostic schemes. Segmentation problems encountered in the remaining 22 images (2.9%) were most often caused by digitization artifacts or poor mammographic technique.


CONCLUSIONS
The developed algorithm can serve as a component of an "intelligent" workstation for computer-aided diagnosis in mammography.
Bick
U
U
Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, University of Chicago, IL, USA.
Giger
M L
ML
Schmidt
R A
RA
Nishikawa
R M
RM
Wolverton
D E
DE
Doi
K
K
D000465:Algorithms; D016477:Artifacts; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D016009:Chi-Square Distribution; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008327:Mammography; D011856:Radiographic Image Enhancement