| 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 | 54 | 2018 |
| 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 | 37 | 2016 |
| 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 | 35 | 2019 |
| 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, 391-397, 2017 | 26 | 2017 |
| ResNet After All: Neural ODEs and Their Numerical Solution K Ott, P Katiyar, P Hennig, M Tiemann International Conference on Learning Representations, 2021 | 24 | 2021 |
| 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 | 11 | 2017 |
| Machine learning identifies stroke features between species S Castaneda-Vega, P Katiyar, F Russo, K Patzwaldt, L Schnabel, ... Theranostics 11, 3017-3034, 2021 | 9 | 2021 |
| When are neural ODE solutions proper ODEs? K Ott, P Katiyar, P Hennig, M Tiemann arXiv preprint arXiv:2007.15386, 2020 | 9 | 2020 |
| 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 | 8 | 2018 |
| Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET–MRI data P Katiyar, J Schwenck, L Frauenfeld, MR Divine, V Agrawal, U Kohlhofer, ... Nature Biomedical Engineering, 1-14, 2023 | 3 | 2023 |
| Improving Augmentation and Evaluation Schemes for Semantic Image Synthesis P Katiyar, A Khoreva arXiv preprint arXiv:2011.12636, 2020 | 2 | 2020 |
| Device and method of training a generative neural network A Khoreva, P Katiyar US Patent App. 17/446,660, 2022 | 1 | 2022 |
| Device and method for operating a neural network AMM Delgado, A Khoreva, L Hoyer, P Katiyar, V Fischer US Patent App. 16/922,544, 2021 | 1 | 2021 |
| Mapping tissue heterogeneity in solid tumours using PET–MRI and machine learning P Katiyar, B Pichler Nature Research Briefing, 2023 | | 2023 |
| Method for determining an output signal by means of a neural network C Blaiotta, P Katiyar US Patent App. 17/652,132, 2022 | | 2022 |
| System and method for training a neural ode network K Ott, M Tiemann, P Katiyar US Patent App. 17/351,772, 2022 | | 2022 |
| Quantification of tumor heterogeneity using PET/MRI and machine learning P Katiyar Universität Tübingen, 2021 | | 2021 |
| PET/MR AM Schmid, P Katiyar, JG Mannheim Imaging Modalities for Biological and Preclinical Research: A Compendium …, 2021 | | 2021 |
| Glioblastoma segmentation using unsupervised machine learning S Castaneda, P Katiyar, J Disselhorst, B Bender, M Reimold, J Hempel, ... Nuklearmedizin-NuclearMedicine 59 (02), P118, 2020 | | 2020 |
| 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 |
Bernd PichlerUniversität TübingenVerified email at med.uni-tuebingen.de
