DocumentCode :
1897649
Title :
Detection of clusters of microcalcification using a k-nearest neighbour classifier
Author :
Hojjatoleslami, S.A. ; Kittler, J.
fYear :
1996
fDate :
35151
Firstpage :
42644
Lastpage :
42649
Abstract :
A method is proposed for the detection of clusters of microcalcifications. The method first segments the image into suspected regions using morphological filters and a new region growing to derive two boundaries for each region. Then a KNN classifier with two different distance measures, Euclidean distance and locally optimum distance measures, is considered for the task of classifying the regions as normal or MC. The last step of the algorithm uses a hierarchical nearest mean clustering method to find the location of clusters of MCs. The performance of the method on a set of normal and abnormal images is then presented
fLanguage :
English
Publisher :
iet
Conference_Titel :
Digital Mammography, IEE Colloquium on
Conference_Location :
London
Type :
conf
DOI :
10.1049/ic:19960493
Filename :
543478
Link To Document :
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