Deep Probabilistic Modeling of Glioma Growth

Jens Petersen, Paul F. Jäger, Fabian Isensee, Simon Kohl, Ulf Neuberger, Wolfgang Wick, Jürgen Debus, Sabine Heiland, Martin Bendszus, Philipp Kickingereder

Type: Preprint

Publication Date: 2019-07-09

Citations: 6

View Publication

Locations

arXiv (Cornell University) - View

Similar Works

Action	Title	Year	Authors
+ PDF Chat	Deep Probabilistic Modeling of Glioma Growth	2019	Jens Petersen Paul F. Jäger Fabian Isensee Simon Kohl Ulf Neuberger Wolfgang Wick Jürgen Debus Sabine Heiland Martin Bendszus Philipp Kickingereder
+	Deep Probabilistic Modeling of Glioma Growth	2019	Jens Petersen Paul F. Jäger Fabian Isensee Simon Kohl Ulf Neuberger Wolfgang Wick Jürgen Debus Sabine Heiland Martin Bendszus Philipp Kickingereder
+	Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction	2023	Qinghui Liu Elies Fuster‐García Ivar Thokle Hovden Donatas Sederevičius Karoline Skogen Bradley J. MacIntosh Edvard Grødem Till Schellhorn Petter Brandal Atle Bjørnerud
+	Continuous-Time Deep Glioma Growth Models	2021	Jens Petersen Fabian Isensee Gregor Köhler Paul F. Jäger David Zimmerer Ulf Neuberger Wolfgang Wick Jürgen Debus Sabine Heiland Martin Bendszus
+	Continuous-Time Deep Glioma Growth Models	2021	Jens Petersen Fabian Isensee Gregor Köhler Paul F. Jäger David Zimmerer Ulf Neuberger Wolfgang Wick Jürgen Debus Sabine Heiland Martin Bendszus
+ PDF Chat	Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?	2022	Corentin Martens Antonin Rovaï Daniele Bonatto Thierry Metens Olivier Debeir Christine Decaestecker Serge Goldman Gaëtan Van Simaeys
+	Deep Learning for Reaction-Diffusion Glioma Growth Modelling: Towards a Fully Personalised Model?	2021	Corentin Martens Antonin Rovaï Daniele Bonatto Thierry Metens Olivier Debeir Christine Decaestecker Serge Goldman Gaëtan Van Simaeys
+	Deep Learning for Reaction-Diffusion Glioma Growth Modelling: Towards a Fully Personalised Model?	2021	Corentin Martens Antonin Rovaï Daniele Bonatto Thierry Metens Olivier Debeir Christine Decaestecker Serge Goldman Gaëtan Van Simaeys
+ PDF Chat	Deep Learning for Reaction-Diffusion Glioma Growth Modelling: Towards a Fully Personalised Model?	2021	Corentin Martens Antonin Rovaï Daniele Bonatto Thierry Metens Olivier Debeir Christine Decaestecker Serge Goldman Gaëtan Van Simaeys
+	Deep learning characterization of brain tumours with diffusion weighted imaging	2022	Cameron Meaney Sunit Das Errol Colak Mohammad Kohandel
+ PDF Chat	Deep Learning Characterization of Brain Tumours With Diffusion Weighted Imaging	2022	Cameron Meaney Sunit Das Errol Colak Mohammad Kohandel
+	Real-time Bayesian personalization via a learnable brain tumor growth model.	2020	Ivan Ezhov Tudor Mot Suprosanna Shit Jana Lipková Johannes C. Paetzold Florian Kofler Fernando Navarro Marie Metz Benedikt Wiestler Bjoern Menze
+ PDF Chat	A Generative Approach for Image-Based Modeling of Tumor Growth	2011	Bjoern Menze Koen Van Leemput Antti Honkela Ender Konukoglu Marc‐André Weber Nicholas Ayache Polina Golland
+	A generative approach for image-based modeling of tumor growth	2011	Bjoern Menze Koen Van Leemput Antti Honkela Ender Konukoglu Marc‐André Weber Nicholas Ayache Polina Golland
+	Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans	2023	Zirui Zhang Ivan Ezhov Michał Balcerak Andy Zhu Benedikt Wiestler Bjoern Menze John Lowengrub
+	A Classification-Based Glioma Diffusion Model Using MRI Data	2006	Marianne Morris Russell Greiner Jörg Sander Albert Murtha Mark Schmidt
+	Diffusion Models for Implicit Image Segmentation Ensembles	2021	Julia Wolleb Robin Sandkühler Florentin Bieder Philippe Valmaggia Philippe C. Cattin
+ PDF Chat	Diffusion Models for Implicit Image Segmentation Ensembles	2021	Julia Wolleb Robin Sandkühler Florentin Bieder Philippe Valmaggia Philippe C. Cattin
+ PDF Chat	Continuous-Time Deep Glioma Growth Models	2021	Jens Petersen Fabian Isensee Gregor Köhler Paul F. Jäger David Zimmerer Ulf Neuberger Wolfgang Wick Jürgen Debus Sabine Heiland Martin Bendszus
+ PDF Chat	Learn-Morph-Infer: A new way of solving the inverse problem for brain tumor modeling	2022	Ivan Ezhov Kevin Scibilia Katharina Franitza Felix Steinbauer Suprosanna Shit Lucas Zimmer Jana Lipková Florian Kofler Johannes C. Paetzold Luca Canalini

Works That Cite This (3)

Action	Title	Year	Authors
+	Real-time Bayesian personalization via a learnable brain tumor growth model.	2020	Ivan Ezhov Tudor Mot Suprosanna Shit Jana Lipková Johannes C. Paetzold Florian Kofler Fernando Navarro Marie Metz Benedikt Wiestler Bjoern Menze
+ PDF Chat	Learning Tumor Growth via Follow-Up Volume Prediction for Lung Nodules	2020	Yamin Li Jiancheng Yang Yi Xu Jingwei Xu Xiaodan Ye Guangyu Tao Xueqian Xie Guixue Liu
+	An Uncertainty-aware Hierarchical Probabilistic Network for Early Prediction, Quantification and Segmentation of Pulmonary Tumour Growth.	2021	Xavier Rafael-Palou Anton Aubanell Mario Ceresa Vicent Ribas Gemma Piella Miguel Á. González Ballester

Works Cited by This (8)

Action	Title	Year	Authors
+ PDF Chat	A Generative Approach for Image-Based Modeling of Tumor Growth	2011	Bjoern Menze Koen Van Leemput Antti Honkela Ender Konukoglu Marc‐André Weber Nicholas Ayache Polina Golland
+	Tumor invasion margin on the Riemannian space of brain fibers	2011	Parisa Mosayebi Dana Cobzaş Albert Murtha Martin Jägersand
+	Glioma follow white matter tracts: a multiscale DTI-based model	2014	Christian Engwer Thomas Hillen Markus Knappitsch Christina Surulescu
+ PDF Chat	Personalized Radiotherapy Planning Based on a Computational Tumor Growth Model	2016	Matthieu Lê Hervé Delingette Jayashree Kalpathy–Cramer Elizabeth R. Gerstner Tracy Batchelor Jan Unkelbach Nicholas Ayache
+ PDF Chat	Image-based modeling of tumor growth in patients with glioma.	2011	Bjoern Menze Erin Stretton Ender Konukoğlu Nicholas Ayache
+ PDF Chat	Convolutional Invasion and Expansion Networks for Tumor Growth Prediction	2017	Ling Zhang Le Lü Ronald M. Summers Electron Kebebew Jianhua Yao
+ PDF Chat	Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference	2019	Jana Lipková Panagiotis Angelikopoulos Stephen Wu Esther Alberts Benedikt Wiestler Christian Diehl Christine Preibisch Thomas Pyka Stephanie E. Combs Panagiotis Hadjidoukas
+	A Probabilistic U-Net for Segmentation of Ambiguous Images	2018	Simon Kohl Bernardino Romera‐Paredes Clemens Meyer Jeffrey De Fauw Joseph R. Ledsam Klaus H. Maier‐Hein S. M. Ali Eslami Danilo Jimenez Rezende Olaf Ronneberger