Haralick Features-Based Classification of Mammograms Using SVM

Author:

Bhateja Vikrant,Gautam Aman,Tiwari Ananya,Bao Le Nguyen,Satapathy Suresh Chandra,Nhu Nguyen Gia,Le Dac-Nhuong

Publisher

Springer Singapore

Reference22 articles.

1. Liu, X., Tang, J.: Mass Classification in Mammograms Using Selected Geometry and Texture Features, and a New SVM-Based Feature Selection Method, In: IEEE Systems Journal, vol. 8, no. 3, Sept. 2014.

2. Jain, A., Singh, S., Bhateja, V.: A Robust Approach for Denoising and Enhancement of Mammographic Breast Masses, In: International Journal on Convergence Computing, vol. 1, no. 1, pp. 38–49, Inderscience Publishers (2013).

3. Morton, M. J., Whaley, D. H., Brandt, K. R., Amrami, K. K.: “Screening mammograms: Interpretation with Computer-Aided Detection-Prospective Evaluation, In: Radiology, vol. 239, no. 2, pp. 375–383, Mar. 2006.

4. Bhateja, V., Urooj, S., Misra, M.: Technical Advancements to Mobile Mammography using Non-Linear Polynomial Filters and IEEE 21451-1 Information Model, In: IEEE Sensors Journal, vol. 15, no. 5, pp. 2559–2566, Advancing Standards for Smart Transducer Interfaces (2015).

5. Wu, S., Yu, S., Yang, Y., Xie, Y.: Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology, In: Computational and Mathematical Methods in Medicine, vol. 2013, pp. 1–8, Hindawi Publishing Corporation (2013).

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