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An unsupervised scheme for detection of microcalcifications on mammograms

DSpace at IIT Bombay

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Field Value
 
Title An unsupervised scheme for detection of microcalcifications on mammograms
 
Creator BHANGALE, TUSHAR
DESAI, UB
SHARMA, UPENDRA
 
Subject band-pass filters
cancer
feature extraction
image recognition
image segmentation
image texture
mammography
 
Description Clusters of microcalcifications which appear like small white grains of sand on mammograms are the earliest signs of breast cancer. In this work we employ a Gabor filter bank for texture analysis of mammograms to detect microcalcifications. A subset of the Gabor filter bank with a certain central frequency and different orientations is used to obtain the Gabor-filtered images. The filtered images are then subjected to a histogram based threshold to obtain binary images. Feature vectors are computed using the binary images. A k-means clustering algorithm with a variance scaled Euclidean distance is used for segmentation of the image.
 
Publisher IEEE
 
Date 2008-12-10T06:37:30Z
2011-11-28T08:42:16Z
2011-12-15T09:57:46Z
2008-12-10T06:37:30Z
2011-11-28T08:42:16Z
2011-12-15T09:57:46Z
2000
 
Type Article
 
Identifier Proceedings of the International Conference on Image Processing (V 1), Vancouver, Canada, 10-13 September 2000, 184-187
0-7803-6297-7
10.1109/ICIP.2000.900925
http://hdl.handle.net/10054/253
http://dspace.library.iitb.ac.in/xmlui/handle/10054/253
 
Language en