A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI
A data-driven approach for analysis of the dynamic contrast enhanced MRI of prostate. No need for pharmacokinetic modeling and knowledge of the arterial input function. LASSO is used to find an optimal set of principal components of the T1 time course. The area under ROC curve increased from 0.78 to 0.86 with the data-driven approach. Prostate cancer probability maps are generated using the proposed features.
prostate cancer dynamic contrast enhanced mri lasso pca svm