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 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 …

[HTML][HTML] Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear partial differential equations

J Bai, GR Liu, A Gupta, L Alzubaidi, XQ Feng… - Computer Methods in …, 2023 - Elsevier
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 …

A clinical decision support system for heart disease prediction using deep learning

AA Almazroi, EA Aldhahri, S Bashir, S Ashfaq - IEEE Access, 2023 - ieeexplore.ieee.org
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 …

[HTML][HTML] Deep learning DCE-MRI parameter estimation: Application in pancreatic cancer

T Ottens, S Barbieri, MR Orton, R Klaassen… - Medical Image …, 2022 - Elsevier
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 …

Self‐supervised IVIM DWI parameter estimation with a physics based forward model

SD Vasylechko, SK Warfield, O Afacan… - Magnetic resonance …, 2022 - Wiley Online Library
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 …

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 …

[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 …

[HTML][HTML] Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning

Á Planchuelo-Gómez, M Descoteaux, H Larochelle… - Medical Image …, 2024 - Elsevier
Diffusion-relaxation MRI aims to extract quantitative measures that characterise
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

MPT Kaandorp, F Zijlstra, C Federau… - Magnetic Resonance …, 2023 - Wiley Online Library
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 …