Improved unsupervised physics‐informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients - Kaandorp, Misha P. T.; Barbieri, Sebastiano; Klaassen, Remy; Laarhoven, Hanneke W. M.; Crezee, Hans; While, Peter T.; Nederveen, Aart J.; Gurney‐Champion, Oliver J. (Magnetic resonance in medicine, 2021)
Keywords: Adenocarcinoma; Algorithms; Artificial neural networks; Bayes Theorem; Bayesian analysis; Cancer; Chemoradiotherapy; Chemotherapy; Coefficient of variation; Computer architecture; Consistency; Deep Learning; deep neural network; Diffusion Magnetic Resonance Imaging; diffusion‐weighted magnetic resonance imaging; Humans; intravoxel incoherent motion; IVIM; Machine learning; Motion; Neural networks; Pancreatic cancer; Pancreatic Neoplasms - diagnostic imaging; Parameters; Patients; Performance evaluation; Physics; Radiation therapy; Reproducibility of Results; s—Computer Processing and Modeling; unsupervised physics‐informed deep learning; pancreatic cancer; IVIM; unsupervised physics-informed deep learning; intravoxel incoherent motion; deep neural network; diffusion-weighted magnetic resonance imaging