Deep learning characterization of brain tumours with diffusion weighted imaging
type: Item
instance of: scholarly article
title: Deep learning characterization of brain tumours with diffusion weighted imaging
zbMATH Open document ID: 1503.92046
author: Cameron Meaney
author: Sunit Das
author: Errol Colak
author: Mohammad Kohandel
published in: Journal of Theoretical Biology
publication date: 2022-12-08T00:00:00Z
Mathematics Subject Classification ID: 92C55
Mathematics Subject Classification ID: 68T07
zbMATH DE Number: 7629226
zbMATH Keywords: deep learning
zbMATH Keywords: cancer
zbMATH Keywords: medical imaging
zbMATH Keywords: applied mathematics
zbMATH Keywords: mathematical oncology
zbMATH Keywords: mathematical medicine
zbMATH Keywords: PDEs
zbMATH Keywords: machine learning
zbMATH Keywords: neural networks
describes a project that uses: FEniCS
describes a project that uses: Adam
describes a project that uses: DOLFIN
MaRDI profile type: Publication
full work available at URL: j.jtbi.2022.111342
OpenAlex ID: W4308519457
cites work: An image-driven parameter estimation problem for a reaction-diffusion glioma growth model with mass effects
cites work: Role of hypoxia-activated prodrugs in combination with radiation therapy: an in silico approach
cites work: Mathematical biology. Vol. 1: An introduction.
cites work: Hidden physics models: machine learning of nonlinear partial differential equations
cites work: Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
cites work: A mathematical model for brain tumor response to radiation therapy
cites work: Image-Driven Biophysical Tumor Growth Model Calibration
DOI: 10.1016/J.JTBI.2022.111342
description: scientific article; zbMATH DE number 7629226