Ensemble inversion for brain tumor growth models with mass effect - Results with BraTS20

Shashank Subramanian, Ali Ghafouri, Klaudius Scheufele, Naveen Himthani, Christos Davatzikos, George Biros

Type: Article

Publication Date: 2022-10-01

Citations: 0

DOI: https://doi.org/10.5281/zenodo.7133594

View Publication

Locations

Zenodo (CERN European Organization for Nuclear Research) - View

Similar Works

Action	Title	Year	Authors
+	A High-Performance Inversion Framework for Brain Tumor Growth Models in Personalized Medicine	2020	Shashank Subramanian Klaudius Scheufele Naveen Himthani George Biros
+	Ensemble Inversion for Brain Tumor Growth Models With Mass Effect	2022	Shashank Subramanian Ali Ghafouri Klaudius Scheufele Naveen Himthani Christos Davatzikos George Biros
+	Ensemble inversion for brain tumor growth models with mass effect	2021	Shashank Subramanian Klaudius Scheufele Naveen Himthani Christos Davatzikos George Biros
+ PDF Chat	Tumor growth model : Parameter estimation and model dedicated to gliomas	2011	Jean-Baptiste Lagaert
+	Mathematical predictions for brain tumor response to novel therapies validated by in vivo and in vitro experiments	2018	Alicia Martínez González
+	Model-based Characterization of Brain Tumor Growth	2019	Daniel Abler Russell C. Rockne Philippe Büchler
+ PDF Chat	From Patient-Specific Mathematical Neuro-Oncology to Precision Medicine	2013	Anne Baldock Russell C. Rockne Anke Boone Maxwell L. Neal Andrea Hawkins‐Daarud D. Corwin Carly A. Bridge Laura Guyman Andrew D. Trister Maciej M. Mrugała
+	Brain tumor growth simulation: model validation through uncertainty quantification	2017	N. Meghdadi Hanieh Niroomand-Oscuii M. Soltani Farzan Ghalichi Mohammad Pourgol‐Mohammad
+	Improved model prediction of glioma growth utilizing tissue-specific boundary effects	2019	Joshua Jacobs Russell C. Rockne Andrea Hawkins‐Daarud Pamela Jackson Sandra K. Johnston Paul E. Kinahan Kristin R. Swanson
+	A review of mechanistic learning in mathematical oncology	2023	John Metzcar Catherine R. Jutzeler Paul Macklin Alvaro Köhn‐Luque Sarah C. Brüningk
+ PDF Chat	Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans	2024	Zirui Zhang Ivan Ezhov Michał Balcerak A. N. Zhu Benedikt Wiestler Bjoern Menze John Lowengrub
+	Clinical implications of in silico mathematical modeling for glioblastoma: a critical review	2017	Maria Protopapa Anna Zygogianni Georgios Stamatakos Christos Antypas Christina Armpilia N.K. Uzunoglu Vassilis Kouloulias
+ PDF Chat	1229 A mechanistic tumor simulator for modeling optimal treatment strategies for diffusely infiltrative tumors: application to glioblastoma	2024	David J. Odde
+	Mathematical modeling and simulation with deep learning methods of cancer growth for patient-specific therapy	2018	Joshua Smith Vishal Kobla Pranav Unni Maziar Raissi Padmanabhan Seshaiyer
+	Data-driven spatio-temporal modelling of glioblastoma	2023	Andreas Christ Sølvsten Jørgensen Ciaran Scott Hill Marc Sturrock Wenhao Tang Saketh R. Karamched Dunja Gorup Mark F. Lythgoe Simona Parrinello Samuel Marguerat Vahid Shahrezaei
+ PDF Chat	Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology	2020	Andreas Mang Spyridon Bakas Shashank Subramanian Christos Davatzikos George Biros
+	Data-driven spatio-temporal modelling of glioblastoma	2022	Andreas Christ Sølvsten Jørgensen Ciaran Scott Hill Marc Sturrock Wenhao Tang Saketh R. Karamched Dunja Gorup Mark F. Lythgoe Simona Parrinello Samuel Marguerat Vahid Shahrezaei
+ PDF Chat	A review of mechanistic learning in mathematical oncology	2024	John Metzcar Catherine R. Jutzeler Paul Macklin Alvaro Köhn‐Luque Sarah C. Brüningk
+	Supplementary Methods from Improved Statistical Modeling of Tumor Growth and Treatment Effect in Preclinical Animal Studies with Highly Heterogeneous Responses <i>In Vivo</i>	2023	Teemu D. Laajala Jukka Corander Niina Saarinen Katja Mäkelä Saija Savolainen Mari I. Suominen Esa Alhoniemi Sari Mäkelä Matti Poutanen Tero Aittokallio
+	Supplementary Methods from Improved Statistical Modeling of Tumor Growth and Treatment Effect in Preclinical Animal Studies with Highly Heterogeneous Responses <i>In Vivo</i>	2023	Teemu D. Laajala Jukka Corander Niina Saarinen Katja Mäkelä Saija Savolainen Mari I. Suominen Esa Alhoniemi Sari Mäkelä Matti Poutanen Tero Aittokallio

Works That Cite This (0)

Action	Title	Year	Authors

Works Cited by This (0)

Action	Title	Year	Authors