Computer-aided diagnosis of clinically significant prostate cancer from MRI images using sparse autoencoder and random forest classifier

• Autorzy: Abraham B. , Nair M. S.

Identyfikatory

DOI

10.1016/j.bbe.2018.06.009

• Języki publikacji: EN

Abstrakty

EN

A novel method to diagnose clinically significant prostate cancer (PCa) using Multi-parametric Magnetic Resonance Imaging (mpMRI) biomarkers in a highly imbalanced dataset is investigated in this paper. Transaxial T2 Weighted (T2W), Apparent Diffusion Coefficient (ADC) and high B-Value (BVAL) Diffusion-Weighted (DW) images obtained from PROSTATEx 2016 challenge dataset publicly available in TCIA (The Cancer Imaging Archive) is used for this study. High-level features are extracted using a single layer Sparse Autoencoder (SAE). Synthetic Minority Oversampling Technique (SMOTE), Weka Resample algorithm and Adaptive Synthetic (ADASYN) sampling approach are explored to solve the class-imbalance problem. The performance of various classifiers are also investigated and it was found that the data augmented using ADASYN followed by classification using random forest classifier achieved the best performance. It achieved an area under ROC curve of 0.979. It also reached a Cohen's kappa score of 0.873, an accuracy of 93.65% and F-Measure of 0.94 in distinguishing clinically significant PCa from indolent Pca.

Słowa kluczowe

EN

Sparse Autoencoder; prostate cancer; multi parametric MRI; ADASYN; random forest

PL

nowotwór gruczołu krokowego; MRI wieloparametryczny; ADASYN; las losowy

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2018
• Tom: Vol. 38, no. 3
• Strony: 733--744
• Opis fizyczny: Bibliogr. 62 poz., rys., tab., wykr.

Twórcy

autor

Abraham B.

• Department of Computer Science, University of Kerala, Kariavattom, Thiruvananthapuram 695581, Kerala, India

autor

Nair M. S.

• Department of Computer Science, Cochin University of Science and Technology, Kochi 682022, Kerala, India

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).