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Article

Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning

Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80208, USA
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Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares Martinsanz, Philip Morrow and Kenji Suzuki
J. Imaging 2016, 2(3), 25; https://doi.org/10.3390/jimaging2030025
Received: 11 May 2016 / Revised: 5 September 2016 / Accepted: 6 September 2016 / Published: 9 September 2016
(This article belongs to the Special Issue Image and Video Processing in Medicine)
The Gleason grading system is generally used for histological grading of prostate cancer. In this paper, we first introduce using the Shearlet transform and its coefficients as texture features for automatic Gleason grading. The Shearlet transform is a mathematical tool defined based on affine systems and can analyze signals at various orientations and scales and detect singularities, such as image edges. These properties make the Shearlet transform more suitable for Gleason grading compared to the other transform-based feature extraction methods, such as Fourier transform, wavelet transform, etc. We also extract color channel histograms and morphological features. These features are the essential building blocks of what pathologists consider when they perform Gleason grading. Then, we use the multiple kernel learning (MKL) algorithm for fusing all three different types of extracted features. We use support vector machines (SVM) equipped with MKL for the classification of prostate slides with different Gleason grades. Using the proposed method, we achieved high classification accuracy in a dataset containing 100 prostate cancer sample images of Gleason Grades 2–5. View Full-Text
Keywords: Gleason grading; multiple kernel learning; prostate cancer; Shearlet transform; texture analysis Gleason grading; multiple kernel learning; prostate cancer; Shearlet transform; texture analysis
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MDPI and ACS Style

Rezaeilouyeh, H.; Mahoor, M.H. Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning. J. Imaging 2016, 2, 25. https://doi.org/10.3390/jimaging2030025

AMA Style

Rezaeilouyeh H, Mahoor MH. Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning. Journal of Imaging. 2016; 2(3):25. https://doi.org/10.3390/jimaging2030025

Chicago/Turabian Style

Rezaeilouyeh, Hadi, and Mohammad H. Mahoor. 2016. "Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning" Journal of Imaging 2, no. 3: 25. https://doi.org/10.3390/jimaging2030025

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