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Prostate cancer localization by novel magnetic resonance dispersion imaging., , , , , and . EMBC, page 2603-2606. IEEE, (2013)Local Density Random Walk Model Preprocessing for Local Shear Wave Viscoelastographic Estimation., , , and . MeMeA, page 1-6. IEEE, (2024)Radiomic combination of spatial and temporal features extracted from DCE-MRI for prostate cancer detection *., , , , , and . EMBC, page 3153-3156. IEEE, (2021)Dynamic velocity vector and relative pressure estimation in the left ventricle with dynamic contrast-enhanced ultrasound of low frame rates., , , , , and . MeMeA, page 1-6. IEEE, (2018)Multiparametric ultrasound and machine learning for prostate cancer localization., , , , , and . EUSIPCO, page 907-911. IEEE, (2022)3D registration of histology and ultrasound data for validation of prostate cancer imaging., , , and . Medical Imaging: Image Processing, volume 8669 of SPIE Proceedings, page 86692T. SPIE, (2013)Prostate cancer risk assessment using a radiogenomic analysis., , , , , , , , , and . MeMeA, page 1-6. IEEE, (2023)Closed-form solution of the convolution integral in the magnetic resonance dispersion model for quantitative assessment of angiogenesis., , , , , and . EMBC, page 4272-4275. IEEE, (2014)Contrast dispersion imaging for cancer localization., and . EMBC, page 4268-4271. IEEE, (2014)