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Shift invariant extrema based feature analysis scheme to discriminate the spiculation nature of mammograms
P. Das,
Published in ISA - Instrumentation, Systems, and Automation Society
2020
PMID: 32216985
Volume: 103
   
Pages: 156 - 165
Abstract
Since uncontrolled growth of malignant masses introduces uneven shape irregularities and spiculations in the boundary, shape representing shift invariant features are essential to resolve the problem of discrimination. However, ambiguous nature of shape, size, margin, orientation of masses produces imprecise feature values. In this view, a new concept of extrema based feature characterization scheme is proposed for capturing radiating nature of mass morphology. Computation of extrema patterns needs only few algorithmic steps. Beside this, present study employs an automated enhancement procedure to improve the classification accuracy. Experimental results show that extrema characterization reduces the feature redundancy to produce high efficiency in reasonably low time. © 2020 ISA
About the journal
JournalISA Transactions
PublisherISA - Instrumentation, Systems, and Automation Society
ISSN00190578