Singular value based characterization and analysis of thermal patches for early breast abnormality detection
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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 same for the DBT-TU-JU database is 92.50% with AUC of 0.9680 using the same classifier. The comparison of the proposed method with the other reported methods concludes that the proposed method outperforms the other existing methods as well as other traditional feature sets used in IBT based breast abnormality detection. Moreover, by using Rank1 and Rank2 singular values, a breast abnormality grading (BAG) index has also been developed for grading the thermograms based on their degree of abnormality.
KeywordsBreast cancer Infrared breast thermography Thermal patches Singular value decomposition Breast abnormality detection Breast abnormality grading
The work presented here is being conducted in the Bio-Medical Infrared Image Processing Laboratory (BMIRD) of Computer Science and Engineering Department, Tripura University (A Central University), Tripura (W). The first author is grateful to Department of Science and Technology (DST), Government of India for providing her Junior Research Fellowship (JRF) under DST INSPIRE fellowship program (No. IF150970). The authors would also like to thank Dr. Gautam Majumdar, Regional Cancer Centre, Agartala Govt. Medical College for his kind support to carry out this work.
This study was funded by Department of Biotechnology (DBT), Government of India (Grant No. BT/533/NE/TBP/2013, Dated 03/03/2014).
Compliance with ethical standards
Conflict of interest
All authors declare that they don’t have any conflict of interest.
This work is done by maintaining the ethical standards of AGMC with IRB approval number F.4 (5-2)/AGMC/Academic/ Project/Research/2007/Sub-I/ 8199-8201.
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