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Reconstruction of high-resolution T2W MR images of the prostate using maximum a posteriori approach and Markov random field regularization.

, , , , , , , , and . SPA, page 96-99. IEEE, (2017)

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On the Effect of DCE MRI Slice Thickness and Noise on Estimated Pharmacokinetic Biomarkers - A Simulation Study., , , and . ICCVG, volume 12334 of Lecture Notes in Computer Science, page 72-86. Springer, (2020)CNN-Based Quantification of Blood Vessels Lumen in 3D Images., , , and . ICCS (2), volume 14074 of Lecture Notes in Computer Science, page 653-661. Springer, (2023)CRF-Based Clustering of Pharmacokinetic Curves from Dynamic Contrast-Enhanced MR Images., , , , , , , , , and 2 other author(s). SPA, page 174-179. IEEE, (2018)Supervised Denoising of Diffusion-Weighted Magnetic Resonance Images Using a Convolutional Neural Network and Transfer Learning., , , , , , and . CoRR, (2022)Phase Correction and Noise-to-Noise Denoising of Diffusion Magnetic Resonance Images Using Neural Networks., , , , and . ICCS (2), volume 14074 of Lecture Notes in Computer Science, page 638-652. Springer, (2023)Improving the Resolution and SNR of Diffusion Magnetic Resonance Images From a Low-Field Scanner., , , and . PCBBE, volume 746 of Lecture Notes in Networks and Systems, page 147-160. Springer, (2023)Dictionary-based through-plane interpolation of prostate cancer T2-weighted MR images., , , , , , , , and . SPA, page 168-173. IEEE, (2018)Reconstruction of high-resolution T2W MR images of the prostate using maximum a posteriori approach and Markov random field regularization., , , , , , , , and . SPA, page 96-99. IEEE, (2017)Using Deep Learning and B-Splines to Model Blood Vessel Lumen from 3D Images., and . Sensors, 24 (3): 846 (February 2024)Rule-based data-driven approach for computer aided diagnosis of the peripheral zone prostate cancer from multiparametric MRI: Proof of concept., , , , , , , , and . SPA, page 90-95. IEEE, (2017)