Prateek Katiyar
Prateek Katiyar
Research Scientist at Bosch Center for Artificial Intelligence
Verified email at de.bosch.com
TitleCited byYear
A population-based Gaussian mixture model incorporating 18F-FDG PET and diffusion-weighted MRI quantifies tumor tissue classes
MR Divine, P Katiyar, U Kohlhofer, L Quintanilla-Martinez, BJ Pichler, ...
Journal of Nuclear Medicine 57 (3), 473-479, 2016
192016
A novel unsupervised segmentation approach quantifies tumor tissue populations using multiparametric MRI: First results with histological validation
P Katiyar, MR Divine, U Kohlhofer, L Quintanilla-Martinez, B Schölkopf, ...
Molecular Imaging and Biology 19 (3), 391-397, 2017
112017
PET/MRI hybrid systems
JG Mannheim, AM Schmid, J Schwenck, P Katiyar, K Herfert, BJ Pichler, ...
Seminars in nuclear medicine 48 (4), 332-347, 2018
92018
Impact of the Arterial Input Function Recording Method on Kinetic Parameters in Small-Animal PET
H Napieczynska, A Kolb, P Katiyar, M Tonietto, M Ud-Dean, R Stumm, ...
Journal of Nuclear Medicine 59 (7), 1159-1164, 2018
42018
Spectral clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG PET: a complement to the standard compartmental modeling approach
P Katiyar, MR Divine, U Kohlhofer, L Quintanilla-Martinez, B Schölkopf, ...
Journal of Nuclear Medicine 58 (4), 651-657, 2017
32017
Grid Saliency for Context Explanations of Semantic Segmentation
L Hoyer, M Munoz, P Katiyar, A Khoreva, V Fischer
Advances in Neural Information Processing Systems (NeurIPS), 2019
2019
Multiparametric analysis of MRI using machine learning allows stroke identification and stroke core prediction
SC Vega, P Katiyar, F Russo, K Partzwaldt, JM Hempel, ...
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM 39, 493-493, 2019
2019
Quantification of tumor heterogeneity using PET/MRI and machine learning
P Katiyar
Universität Tübingen, 0
Grid Saliency for Context Explanations of Semantic Segmentation Supplementary Material
L Hoyer, M Munoz, P Katiyar, A Khoreva, V Fischer
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