Deep learning for registration of high-resolution 3D brain images
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Abdullah Nazib Thesis
(PDF 23MB)
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. |
Description
This thesis is a comprehensive study, evaluation and experimentation of image registration tools for high-resolution tissue-cleared images. Tissue Clearing allows 3D imaging of whole brains at the single cell resolution. The thesis examines conventional image registration tools and identifies their limited ability to handle such samples. Based on these findings, the thesis dedicates its investigation on more efficient and accurate algorithm development for the registration of tissue-cleared 3D images. A number of deep-learning based methods are tested and shown to be very efficient compared to their conventional counterparts.
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| ID Code: | 204293 |
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| Item Type: | QUT Thesis (PhD) |
| Supervisor: | Perrin, Dimitri & Fookes, Clinton |
| Keywords: | Image Registration, High Resolution, Deep Learning, Tissue Clearing, Medical Image, CUBIC |
| DOI: | 10.5204/thesis.eprints.204293 |
| Divisions: | Past > QUT Faculties & Divisions > Science & Engineering Faculty Current > Schools > School of Mathematical Sciences |
| Institution: | Queensland University of Technology |
| Deposited On: | 08 Oct 2020 07:16 |
| Last Modified: | 08 Oct 2020 07:16 |
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