A Classification-Based Glioma Diffusion Model Using MRI Data
| Autor: | Mark Schmidt, Russell Greiner, Jörg Sander, Marianne Morris, Albert Murtha |
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| Rok vydání: | 2006 |
| Předmět: |
Artificial neural network
Computer science business.industry Supervised learning Central nervous system Pattern recognition Glioma cell Grey matter medicine.disease computer.software_genre White matter medicine.anatomical_structure Voxel Glioma medicine Artificial intelligence Diffusion (business) business computer |
| Zdroj: | Advances in Artificial Intelligence ISBN: 9783540220046 Canadian Conference on AI |
| Popis: | Gliomas are diffuse, invasive brain tumors. We propose a 3D classification-based diffusion model, CDM, that predicts how a glioma will grow at a voxel-level, on the basis of features specific to the patient, properties of the tumor, and attributes of that voxel. We use Supervised Learning algorithms to learn this general model, by observing the growth patterns of gliomas from other patients. Our empirical results on clinical data demonstrate that our learned CDM model can, in most cases, predict glioma growth more effectively than two standard models: uniform radial growth across all tissue types, and another that assumes faster diffusion in white matter. |
| Databáze: | OpenAIRE |
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