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We propose a curve-based Riemannian-geometric approach for general shape-based statistical analyses of tumors obtained from radiologic images. A key component of the framework is a suitable metric that (1) enables comparisons of tumor…

Applications · Statistics 2017-02-07 Karthik Bharath , Sebastian Kurtek , Arvind Rao , Veerabhadran Baladandayuthapani

The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the preoperative tumor volume is essential. Volumetric assessment of tumor volume with manual…

Computer Vision and Pattern Recognition · Computer Science 2011-03-11 Jan Egger , Dženan Zukić , Miriam H. A. Bauer , Daniela Kuhnt , Barbara Carl , Bernd Freisleben , Andreas Kolb , Christopher Nimsky

Glioblastoma Multiforme is a malignant brain tumor with poor prognosis. There have been numerous attempts to model the invasion of tumorous glioma cells via partial differential equations in the form of advection-diffusion-reaction…

Cell Behavior · Quantitative Biology 2020-01-16 Christian Engwer , Michael Wenske

Deep learning has significantly advanced automated brain tumor diagnosis, yet clinical adoption remains limited by interpretability and computational constraints. Conventional models often act as opaque ''black boxes'' and fail to quantify…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Sepehr Salem Ghahfarokhi , M. Moein Esfahani , Raj Sunderraman , Vince Calhoun , Mohammed Alser

Precise prognostic modeling of glioblastoma (GBM) under varying treatment interventions is essential for optimizing clinical outcomes. While generative AI has shown promise in simulating GBM evolution, existing methods typically treat…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Chenhui Wang , Boyun Zheng , Liuxin Bao , Zhihao Peng , Peter Y. M. Woo , Hongming Shan , Yixuan Yuan

Glioblastoma multiforme (GBM), the most aggressive primary brain tumour, exhibits low survival rates due to its rapid growth, infiltrates surrounding brain tissue, and is highly resistant to treatment. One major challenge is oedema…

Gliomas constitute one of the most aggressive and heterogeneous forms of brain tumors, posing major challenges for understanding their biology and developing effective treatments. Animal models enable the collection of rich longitudinal…

In the present work we consider the mathematical model that describes brain tumour growth (glioblastomas) under medical treatment. Based on the medical study presented by R. Stupp et al. (New Engl Journal of Med 352: 987-996, 2005) which…

Tissues and Organs · Quantitative Biology 2016-10-25 O. Gonzalez-Gaxiola , R. Bernal-Jaquez

We present a multi-species partial differential equation (PDE) model for tumor growth and a an algorithm for calibrating the model from magnetic resonance imaging (MRI) scans. The model is designed for glioblastoma (GBM) brain tumors. The…

Numerical Analysis · Mathematics 2024-08-27 Ali Ghafouri , George Biros

We propose a method for extracting physics-based biomarkers from a single multiparametric Magnetic Resonance Imaging (mpMRI) scan bearing a glioma tumor. We account for mass effect, the deformation of brain parenchyma due to the growing…

Accurate prognosis for Glioblastoma (GBM) using deep learning (DL) is hindered by extreme spatial and structural heterogeneity. Moreover, inconsistent MRI acquisition protocols across institutions hinder generalizability of models.…

Machine Learning · Computer Science 2026-02-13 Ankita Paul , Wenyi Wang

Gliomas are the most common primary brain tumors, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the preoperative tumor volume is essential. Volumetric assessment of tumor volume with manual…

Computational Engineering, Finance, and Science · Computer Science 2011-03-10 Jan Egger , Miriam H. A. Bauer , Daniela Kuhnt , Christoph Kappus , Barbara Carl , Bernd Freisleben , Christopher Nimsky

Mathematical modelling of tumor growth is one of the most useful and inexpensive approaches to determine and predict the stage, size and progression of tumors in realistic geometries. Moreover, these models has been used to get an insight…

Medical Physics · Physics 2017-08-01 Miguel Martín-Landrove

Glioblastoma is the most common primary adult brain tumor, with a grim prognosis - median survival of 12-18 months following treatment, and 4 months otherwise. Glioblastoma is widely infiltrative in the cerebral hemispheres and well-defined…

We developed a mathematical model to simulate the growth of tumor volume and its response to a single fraction of high dose irradiation. We made several key assumptions of the model. Tumor volume is composed of proliferating (or dividing)…

Medical Physics · Physics 2015-11-13 Yoichi Watanabe , Erik L. Dahlman , Kevin Z. Leder , Susanta K. Hui

Glioblastoma multiforme (GBM) is a fast-growing and highly invasive brain tumour, it tends to occur in adults between the ages of 45 and 70 and it accounts for 52 percent of all primary brain tumours. Usually, GBMs are detected by magnetic…

Image and Video Processing · Electrical Eng. & Systems 2020-04-21 Matteo Rucco , Lorenzo Falsetti , Giovanna Viticchi

Tumor growth has long been a target of investigation within the context of mathematical and computer modelling. The objective of this study is to propose and analyze a two-dimensional probabilistic cellular automata model to describe…

Tissues and Organs · Quantitative Biology 2009-11-13 E. A. Reis , L. B. L. Santos , S. T. R. Pinho

In this paper we analyse a differential system related to a Glioblastoma growth. Using numerical simulations, we prove that model captures different kind of growth changing adequately the parameters of the model. Firstly, we make an…

Analysis of PDEs · Mathematics 2021-09-21 A. Fernández-Romero , F. Guillén-González , A. Suárez

The glioblastoma multiforme is the most common malignant primary brain tumor and is one of the highest malignant human neoplasms. During the course of disease, the evaluation of tumor volume is an essential part of the clinical follow-up.…

Computer Vision and Pattern Recognition · Computer Science 2011-03-10 Jan Egger , Miriam H. A. Bauer , Daniela Kuhnt , Barbara Carl , Christoph Kappus , Bernd Freisleben , Christopher Nimsky

In this article, we present a multispecies reaction-advection-diffusion partial differential equation (PDE) coupled with linear elasticity for modeling tumor growth. The model aims to capture the phenomenological features of glioblastoma…

Medical Physics · Physics 2019-05-28 Shashank Subramanian , Amir Gholami , George Biros