What is it about?
Computer Aided Diagnosis (CAD) for prostate cancer detection in MRI using feature extraction and an unsupervised clustering method.
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Why is it important?
Unsupervised Computer Aided Diagnosis method is important to minimize the user interaction with the system. From clinical point of view, CAD plays an important role as a second opinion for radiologists. CAD can reduce the variability among radiologists, speeds up the diagnostic decision making as well as improve sensitivity and specificity.
Perspectives
The proposed method is among a few unsupervised CAD method in the literature. This method uses only 4 texture features but can produce similar results with the ones based on multiparametric MRIs and machine learning algorithms.
Mr Andrik Rampun
Aberystwyth University
Read the Original
This page is a summary of: Computer-aided diagnosis: detection and localization of prostate cancer within the peripheral zone, International Journal for Numerical Methods in Biomedical Engineering, September 2015, Wiley,
DOI: 10.1002/cnm.2745.
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