Synthetic 3D brain MRI generation for evaluation and improvement of cortical thickness estimation methods
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Filip Rusak Thesis.pdf. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. |
Description
This thesis was a step forward in developing tools and methods for very accurate measurements of brain atrophy which is essential for studying neurodegenerative diseases. The proposed methods are based on generative artificial intelligence (AI) that utilises cortex meshes to introduce controlled and quantified changes in different brain regions. This thesis provided the world-first benchmark for methods measuring cortical thinning and enabled the research community to evaluate their cortical thickness estimation methods against it.
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| ID Code: | 238363 | ||
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| Item Type: | QUT Thesis (PhD) | ||
| Supervisor: | Bradley, Andrew P. & Fookes, Clinton | ||
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| Keywords: | 3D Synthetic Brain MRI, Generative adversarial networks, Synthetic atrophy, Data augmentation, Partial volume maps, Cortical thickness estimation | ||
| DOI: | 10.5204/thesis.eprints.238363 | ||
| Pure ID: | 126525560 | ||
| Divisions: | Current > QUT Faculties and Divisions > Faculty of Engineering Current > Schools > School of Electrical Engineering & Robotics |
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| Institution: | Queensland University of Technology | ||
| Deposited On: | 03 Mar 2023 05:24 | ||
| Last Modified: | 03 Mar 2023 05:24 |
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