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Prateek Katiyar

Showing results (1-10 of 7) with videos related to

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Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|December 15, 2015
A Population-Based Gaussian Mixture Model Incorporating 18F-FDG PET and Diffusion-Weighted MRI Quantifies Tumor Tissue ClassesMathew R Divine, Prateek Katiyar, Ursula Kohlhofer, et al.
Molecular Imaging and Biology|October 14, 2016
A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological ValidationPrateek Katiyar, Mathew R Divine, Ursula Kohlhofer, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|November 5, 2016
Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic <sup>18</sup>F-FDG PET: A Complement to the Standard Compartmental Modeling ApproachPrateek Katiyar, Mathew R Divine, Ursula Kohlhofer, et al.
Seminars in Nuclear Medicine|June 2, 2018
PET/MRI Hybrid SystemsJulia G Mannheim, Andreas M Schmid, Johannes Schwenck, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|February 25, 2018
Impact of the Arterial Input Function Recording Method on Kinetic Parameters in Small-Animal PETHanna Napieczynska, Armin Kolb, Prateek Katiyar, et al.
Nature Biomedical Engineering|June 5, 2023
Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET-MRI dataPrateek Katiyar, Johannes Schwenck, Leonie Frauenfeld, et al.
Theranostics|January 18, 2021
Machine learning identifies stroke features between speciesSalvador Castaneda-Vega, Prateek Katiyar, Francesca Russo, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|December 15, 2015
A Population-Based Gaussian Mixture Model Incorporating 18F-FDG PET and Diffusion-Weighted MRI Quantifies Tumor Tissue ClassesMathew R Divine, Prateek Katiyar, Ursula Kohlhofer, et al.
Molecular Imaging and Biology|October 14, 2016
A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological ValidationPrateek Katiyar, Mathew R Divine, Ursula Kohlhofer, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|November 5, 2016
Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic <sup>18</sup>F-FDG PET: A Complement to the Standard Compartmental Modeling ApproachPrateek Katiyar, Mathew R Divine, Ursula Kohlhofer, et al.
Seminars in Nuclear Medicine|June 2, 2018
PET/MRI Hybrid SystemsJulia G Mannheim, Andreas M Schmid, Johannes Schwenck, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|February 25, 2018
Impact of the Arterial Input Function Recording Method on Kinetic Parameters in Small-Animal PETHanna Napieczynska, Armin Kolb, Prateek Katiyar, et al.
Nature Biomedical Engineering|June 5, 2023
Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET-MRI dataPrateek Katiyar, Johannes Schwenck, Leonie Frauenfeld, et al.
Theranostics|January 18, 2021
Machine learning identifies stroke features between speciesSalvador Castaneda-Vega, Prateek Katiyar, Francesca Russo, et al.
Pageof 1