Author(s):
1. Zobia Suhail:
Department of Computer Science, Faculty of Computing and Information Technology, University of the Punjab,,Pakistan
2. Reyer Zwiggelaar:
Department of Computer Science, Aberystwyth University,Aberstwyth, Wales,U.K
Abstract:
In this paper we present a new approach for the classification of benign and malignant micro-calcification clusters by transforming data from the image to the text domain. A string representation is extracted from binary micro-calcification segmentation images. We extracted two diferent features from the strings and combined diferent machine learning techniques towards benign versus malignant classification. We evaluated our proposed method on the DDSM database and experimental results indicates a Classification Accuracy equal to 92%.
Page(s):
113-123
Published:
Journal: VAWKUM Transactions on Computer Sciences, Volume: 11, Issue: 2, Year: 2023
Keywords:
Classification
,
Malignant
,
Benign
,
Image features
,
String matching
,
Microcalcification
References:
References are not available for this document.
Citations
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