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2021 | OriginalPaper | Chapter

A Compact Shape Descriptor Using Empirical Mode Decomposition to Detect Malignancy in Breast Tumour

Authors : Spandana Paramkusham, Manjula Sri Rayudu, Puja S. Prasad

Published in: Advanced Computing

Publisher: Springer Singapore

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Abstract

Breast cancer is the most common cancer in India and the world. Mammogram helps the radiologists to detect abnormalities in breast. Analysis of the lesions on breast helps doctors in the detection of cancer in early stages. Lesion contours of breast are characterized by their shape. Malignant lesion contours have speculated and ill-defined shapes and benign have circular and lobulated shape. In the present work, we proposed a method to classify breast contours into benign/malignant using empirical mode decomposition (EMD) technique. Initially, the two-dimension contours of breast lesions are compacted into 1D signature. Further, 1D signatures of lesions are decomposed into intrinsic mode functions (IMFs) by the EMD algorithm and statistical based features are calculated from these IMFs. This parameters form a input feature vector which are further fed to classifier.

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Metadata
Title
A Compact Shape Descriptor Using Empirical Mode Decomposition to Detect Malignancy in Breast Tumour
Authors
Spandana Paramkusham
Manjula Sri Rayudu
Puja S. Prasad
Copyright Year
2021
Publisher
Springer Singapore
Book
Advanced Computing

Print ISBN: 978-981-16-0400-3

Electronic ISBN: 978-981-16-0401-0

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-0401-0_5

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