Title
Does intensity windowing improve the detection of simulated calcifications in dense mammograms?
Abstract
This study attempts to determine whether intensity windowing (IW) improves detection of simulated calcifications in dense mammograms. Clusters of five simulated calcifications were embedded in dense mammograms digitized at 50-μm pixels, 12 bits deep. Film images with no windowing applied were compared with film images with nine different window widths and levels applied. A simulated cluster was embedded in a realistic background of dense breast tissue, with the position of the cluster varied. The key variables involved in each trial included the position of the cluster, contrast level of the cluster, and the IW settings applied to the image. Combining the ten IW conditions, four contrast levels and four quadrant positions gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 160 backgrounds. The entire experiment consisted of 800 trials. Twenty student observers were asked to detect the quadrant of the image in which the mass was located. There was a statistically significant improvement in detection performance for clusters of calcifications when the window width was set at 1024 with a level of 3328, and when the window width was set at 1024 with a level of 3456. The selected IW settings should be tested in the clinic with digital mammograms to determine whether calcification detection performance can be improved.
Year
DOI
Venue
1997
10.1007/BF03168559
J. Digital Imaging
Keywords
Field
DocType
mammography,image processing,intensity windowing,observer studies,calcifications,computers,radiology
Computer vision,Mammography,Computer science,Window Width,Image processing,Pixel,Artificial intelligence,Radiology,Radiographic Image Enhancement
Journal
Volume
Issue
ISSN
10
2
0897-1889
Citations 
PageRank 
References 
3
1.78
1
Authors
9
Name
Order
Citations
PageRank
Etta D. Pisano134449.06
Jayanthi Chandramouli253.28
Bradley M. Hemminger345638.24
Marla DeLuca4915.55
Deb Glueck553.28
R. Eugene Johnston611815.87
Keith Muller715813.40
M. Patricia Braeuning8937.04
Stephen M. Pizer92000262.21