Sridevi, V (2020) Advancement on Breast Cancer Detection Using Medio-Lateral-Oblique (Mlo) and Cranio-Caudal (CC) Features. Advancement on Breast Cancer Detection Using Medio-Lateral-Oblique (Mlo) and Cranio-Caudal (CC) Features, 83. pp. 85-93. ISSN 0193-4120
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Jan 2020 - Advancement on Breast Cancer Detection Using Medio-Lateral-Oblique (Mlo) and Cranio-Caudal (CC) Features pdf.pdf - Published Version
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Abstract
The purpose of this paper is to diagnose accurately the breast cancer for which a a
computer aided diagnostic system (CAD) is being proposed. In this paper two types of
views are used to enhance diagnostic efficiency, such as cranio-caudal (CC) and medio
lateral-oblique (MLO). This paper involves segmentation, feature extraction and
classification of images. Adaptive K means clustering method is used in segmentation
to segment the two views from a mammogram image. The combination of conventional
k-means clustering method and Gabor filter is employed in the feature extraction stage
to extract the features of CC and MLO views. Finally, Knn classifier is used to classify
the mammogram image into four ways, such as CC-Normal, CC-Malignant, MLO
Normal and MLO-malignant.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Segmentation, Adaptive K-means clustering, Feature extraction, conventional K-means clustering, Gabor filter, Classification, Knn classifier |
| Divisions: | PSG College of Arts and Science > Department of Computer Science |
| Depositing User: | Mr Team Mosys |
| Date Deposited: | 06 Oct 2025 06:27 |
| Last Modified: | 06 Oct 2025 06:27 |
| URI: | https://ir.psgcas.ac.in/id/eprint/2456 |
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