Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives
The rapid development of artificial intelligence (AI) has gained importance, with many tools
already entering our daily lives. The medical field of radiation oncology is also subject to this …
already entering our daily lives. The medical field of radiation oncology is also subject to this …
Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans
Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for
understanding tumor growth dynamics and designing personalized radiotherapy treatment …
understanding tumor growth dynamics and designing personalized radiotherapy treatment …
Solving inverse problems in physics by optimizing a discrete loss: Fast and accurate learning without neural networks
In recent years, advances in computing hardware and computational methods have
prompted a wealth of activities for solving inverse problems in physics. These problems are …
prompted a wealth of activities for solving inverse problems in physics. These problems are …
Diffusion tensor transformation for personalizing target volumes in radiation therapy
Diffusion tensor imaging (DTI) is used in tumor growth models to provide information on the
infiltration pathways of tumor cells into the surrounding brain tissue. When a patient-specific …
infiltration pathways of tumor cells into the surrounding brain tissue. When a patient-specific …
A Learnable Prior Improves Inverse Tumor Growth Modeling
Biophysical modeling, particularly involving partial differential equations (PDEs), offers
significant potential for tailoring disease treatment protocols to individual patients. However …
significant potential for tailoring disease treatment protocols to individual patients. However …
A novel, finite-element-based framework for sparse data solution reconstruction and multiple choices
W Bielajewa, M Baxter, P Nithiarasu - arXiv preprint arXiv:2410.06386, 2024 - arxiv.org
Digital twinning offers a capability of effective real-time monitoring and control, which are
vital for cost-intensive experimental facilities, particularly the ones where extreme conditions …
vital for cost-intensive experimental facilities, particularly the ones where extreme conditions …
Spatial Brain Tumor Concentration Estimation for Individualized Radiotherapy Planning
Biophysical modeling of brain tumors has emerged as a promising strategy for personalizing
radiotherapy planning by estimating the otherwise hidden distribution of tumor cells within …
radiotherapy planning by estimating the otherwise hidden distribution of tumor cells within …
BILO: BILEVEL LOCAL OPERATOR LEARNING FOR
PDE INVERSE - openreview.net
We propose a new neural network based method for solving inverse problems for partial
differential equations (PDEs) by formulating the PDE inverse problem as a bilevel …
differential equations (PDEs) by formulating the PDE inverse problem as a bilevel …