Mammogram Classification Using Discrete Wavelet Transform Features and a Novel Vector Quantization Technique for Breast Cancer Detection
Ahmad M. Sarhan, Radaan A. Al-Dosari
Current Journal of Applied Science and Technology · pp. 1–14 · Published 16 Feb 2017
10.9734/BJAST/2017/30420Abstract
In this paper, a digital mammogram classification system is presented. The proposed system uses the Discrete Wavelet Transform (DWT) to obtain features from the input mammogram image. The proposed system suggests a new algorithm for generating the codebook used by the vector quantization (VQ) algorithm to classify the input mammogram (malignant, benign, or normal). The obtained results on the DDSM database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches. Simulation results show that the proposed system achieves a high accuracy and sensitivity.
Cited by 4
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Ahmad M. Sarhan · Journal of Biomedical Science and Engineering · 2020
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Pramit Brata Chanda, Subir Kumar Sarkar · 2020 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) · 2020
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