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Computer-Aided Detection and Diagnosis of Thyroid Nodules Using Machine and Deep Learning Classification Algorithms.
- Source :
- IETE Journal of Research; Feb2023, Vol. 69 Issue 2, p995-1006, 12p
- Publication Year :
- 2023
-
Abstract
- This paper proposes a computer-aided methodology for detecting and segmenting the tumor regions in ultrasound thyroid images using machine and deep learning algorithms. This proposed tumor detection methodology uses Kirsch's edge detector for enhancing the edge region pixels in thyroid image and then Dual Tree Contourlet Transform (DTCT) was applied on the enhanced image for obtaining the coefficients. Then, features are computed from this transformed thyroid image and these features are trained and classified using the Co-Active Adaptive Neuro Expert System (CANFES) classifier. Then, the morphological segmentation method is applied on the abnormal thyroid image to segment the tumor regions. Finally, the Convolutional Neural Network (CNN) algorithm is applied on the segmented tumor regions for diagnosing them into mild, moderate and severe. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03772063
- Volume :
- 69
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- IETE Journal of Research
- Publication Type :
- Academic Journal
- Accession number :
- 162174137
- Full Text :
- https://doi.org/10.1080/03772063.2020.1844083