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Artificial intelligence in pancreatic cancer
B Huang, H Huang, S Zhang, D Zhang, Q Shi… - …, 2022 - pmc.ncbi.nlm.nih.gov
Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%.
The pancreatic cancer patients diagnosed with early screening have a median overall …
The pancreatic cancer patients diagnosed with early screening have a median overall …
The future of MRI in radiation therapy: Challenges and opportunities for the MR community
RJ Goodburn, MEP Philippens… - Magnetic resonance …, 2022 - Wiley Online Library
Radiation therapy is a major component of cancer treatment pathways worldwide. The main
aim of this treatment is to achieve tumor control through the delivery of ionizing radiation …
aim of this treatment is to achieve tumor control through the delivery of ionizing radiation …
[HTML][HTML] Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear partial differential equations
Our recent study has found that physics-informed neural networks (PINN) tend to be local
approximators after training. This observation led to the development of a novel physics …
approximators after training. This observation led to the development of a novel physics …
A clinical decision support system for heart disease prediction using deep learning
Unfortunately, heart disease is currently the primary cause of mortality worldwide and its
incidence is increasing. Detecting heart disease in its initial stages before a cardiac event …
incidence is increasing. Detecting heart disease in its initial stages before a cardiac event …
[HTML][HTML] Deep learning DCE-MRI parameter estimation: Application in pancreatic cancer
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an MRI technique
for quantifying perfusion that can be used in clinical applications for classification of tumours …
for quantifying perfusion that can be used in clinical applications for classification of tumours …
Self‐supervised IVIM DWI parameter estimation with a physics based forward model
Purpose To assess the robustness and repeatability of intravoxel incoherent motion model
(IVIM) parameter estimation for the diffusion‐weighted MRI in the abdominal organs under …
(IVIM) parameter estimation for the diffusion‐weighted MRI in the abdominal organs under …
Probing renal microstructure and function with advanced diffusion MRI: concepts, applications, challenges, and future directions
J Stabinska, HJ Wittsack, LO Lerman… - Journal of Magnetic …, 2024 - Wiley Online Library
Diffusion measurements in the kidney are affected not only by renal microstructure but also
by physiological processes (ie, glomerular filtration, water reabsorption, and urine …
by physiological processes (ie, glomerular filtration, water reabsorption, and urine …
[HTML][HTML] Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter
JP de Almeida Martins, M Nilsson, B Lampinen… - NeuroImage, 2021 - Elsevier
Specific features of white matter microstructure can be investigated by using biophysical
models to interpret relaxation-diffusion MRI brain data. Although more intricate models have …
models to interpret relaxation-diffusion MRI brain data. Although more intricate models have …
[HTML][HTML] Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning
Diffusion-relaxation MRI aims to extract quantitative measures that characterise
microstructural tissue properties such as orientation, size, and shape, but long acquisition …
microstructural tissue properties such as orientation, size, and shape, but long acquisition …
Deep learning intravoxel incoherent motion modeling: Exploring the impact of training features and learning strategies
Purpose The development of advanced estimators for intravoxel incoherent motion (IVIM)
modeling is often motivated by a desire to produce smoother parameter maps than least …
modeling is often motivated by a desire to produce smoother parameter maps than least …