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LINPE-BL: A Local Descriptor and Broad Learning for Identification of Abnormal Breast Thermograms.
- Source :
-
IEEE Transactions on Medical Imaging . Dec2021, Vol. 40 Issue 12, p3919-3931. 13p. - Publication Year :
- 2021
-
Abstract
- This paper proposes a novel local feature descriptor coined as a local instant-and-center-symmetric neighbor-based pattern of the extrema-images (LINPE) to detect breast abnormalities in thermal breast images. It is a hybrid descriptor that combines two different feature descriptors: one is the inverse-probability difference extrema (IpDE), and another is the local instant and center-symmetric neighbor-based pattern (LICsNP). IpDE is developed to compute the intensity-inhomogeneity-invariant feature-based image of the breast thermogram. Besides, the LICsNP is intended to capture the local microstructure pattern information in the IpDE image. A new paradigm, named Broad Learning (BL) network, is introduced here as a classifier to differentiate the healthy and sick breast thermograms efficiently. The efficacy of the proposed system is quantitatively validated on the images of DMR-IR and DBT-TU-JU databases. Extensive experimentation on these databases with an average accuracy of 96.90% and 94%, respectively, justifies proposed system’s superiority in the differentiation of healthy and sick breast thermograms over the other related existing state-of-the-art methods. The proposed system also performs consistently in the presence of noise and rotational changes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02780062
- Volume :
- 40
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Medical Imaging
- Publication Type :
- Academic Journal
- Accession number :
- 153925705
- Full Text :
- https://doi.org/10.1109/TMI.2021.3101453