Literature DB >> 17633740

A recursive anisotropic fast marching approach to reaction diffusion equation: application to tumor growth modeling.

Ender Konukoglu1, Maxime Sermesant, Olivier Clatz, Jean-Marc Peyrat, Hervé Delingette, Nicholas Ayache.   

Abstract

Bridging the gap between clinical applications and mathematical models is one of the new challenges of medical image analysis. In this paper, we propose an efficient and accurate algorithm to solve anisotropic Eikonal equations, in order to link biological models using reaction-diffusion equations to clinical observations, such as medical images. The example application we use to demonstrate our methodology is tumor growth modeling. We simulate the motion of the tumor front visible in images and give preliminary results by solving the derived anisotropic Eikonal equation with the recursive fast marching algorithm.

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Year:  2007        PMID: 17633740     DOI: 10.1007/978-3-540-73273-0_57

Source DB:  PubMed          Journal:  Inf Process Med Imaging        ISSN: 1011-2499


  7 in total

1.  Inference of Cerebrovascular Topology With Geodesic Minimum Spanning Trees.

Authors:  Stefano Moriconi; Maria A Zuluaga; H Rolf Jager; Parashkev Nachev; Sebastien Ourselin; M Jorge Cardoso
Journal:  IEEE Trans Med Imaging       Date:  2018-07-26       Impact factor: 10.048

2.  Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?

Authors:  Corentin Martens; Antonin Rovai; Daniele Bonatto; Thierry Metens; Olivier Debeir; Christine Decaestecker; Serge Goldman; Gaetan Van Simaeys
Journal:  Cancers (Basel)       Date:  2022-05-20       Impact factor: 6.575

Review 3.  In silico cancer modeling: is it ready for prime time?

Authors:  Thomas S Deisboeck; Le Zhang; Jeongah Yoon; Jose Costa
Journal:  Nat Clin Pract Oncol       Date:  2008-10-14

4.  Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI.

Authors:  Nathan Gaw; Andrea Hawkins-Daarud; Leland S Hu; Hyunsoo Yoon; Lujia Wang; Yanzhe Xu; Pamela R Jackson; Kyle W Singleton; Leslie C Baxter; Jennifer Eschbacher; Ashlyn Gonzales; Ashley Nespodzany; Kris Smith; Peter Nakaji; J Ross Mitchell; Teresa Wu; Kristin R Swanson; Jing Li
Journal:  Sci Rep       Date:  2019-07-11       Impact factor: 4.379

5.  Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study.

Authors:  Corentin Martens; Laetitia Lebrun; Christine Decaestecker; Thomas Vandamme; Yves-Rémi Van Eycke; Antonin Rovai; Thierry Metens; Olivier Debeir; Serge Goldman; Isabelle Salmon; Gaetan Van Simaeys
Journal:  Tomography       Date:  2021-10-29

Review 6.  Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate.

Authors:  Sam Coveney; Chris Cantwell; Caroline Roney
Journal:  Med Biol Eng Comput       Date:  2022-07-22       Impact factor: 3.079

7.  Modelling non-homogeneous stochastic reaction-diffusion systems: the case study of gemcitabine-treated non-small cell lung cancer growth.

Authors:  Paola Lecca; Daniele Morpurgo
Journal:  BMC Bioinformatics       Date:  2012-09-07       Impact factor: 3.169

  7 in total

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