Singular value based characterization and analysis of thermal patches for early breast abnormality detection

Australasian Physical & Engineering Sciences in Medicine
Usha Rani GogoiAnjan Kumar Ghosh

Abstract

The purpose of this study is to develop a novel breast abnormality detection system by utilizing the potential of infrared breast thermography (IBT) in early breast abnormality detection. Since the temperature distributions are different in normal and abnormal thermograms and hot thermal patches are visible in abnormal thermograms, the abnormal thermograms possess more complex information than the normal thermograms. Here, the proposed method exploits the presence of hot thermal patches and vascular changes by using the power law transformation for pre-processing and singular value decomposition to characterize the thermal patches. The extracted singular values are found to be statistically significant (p < 0.001) in breast abnormality detection. The discriminability of the singular values is evaluated by using seven different classifiers incorporating tenfold cross-validations, where the thermograms of the Department of Biotechnology-Tripura University-Jadavpur University (DBT-TU-JU) and Database of Mastology Research (DMR) databases are used. In DMR database, the highest classification accuracy of 98.00% with the area under the ROC curve (AUC) of 0.9862 is achieved with the support vector machine using polynomial kernel. The ...Continue Reading

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Citations

Dec 22, 2019·Sensors·Olivia Vargas-LopezCarlos A Perez-Ramirez
Sep 24, 2019·Journal of Medical Engineering & Technology·J Zuluaga-GomezC Varnier
Mar 31, 2021·Computer Methods and Programs in Biomedicine·Raquel Sánchez-CauceManuel Luque

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Methods Mentioned

BETA
feature extraction
X-ray

Software Mentioned

SVM
Poly
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