Bayesian segmentation and restoration of magnetic resonance brain images
My objective in this research is to develop and extend existing image restora-tion techniques by introducing more powerful image models for MR images. The approach shall also be automated, data-driven, and require very minimal inter-ference from users so that neurologists can concerntrate on their j...
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sg-ntu-dr.10356-24542023-03-04T00:33:00Z Bayesian segmentation and restoration of magnetic resonance brain images Tan, Choong Leong. Rajapakse, Jagath Chandana School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences My objective in this research is to develop and extend existing image restora-tion techniques by introducing more powerful image models for MR images. The approach shall also be automated, data-driven, and require very minimal inter-ference from users so that neurologists can concerntrate on their job of analysing the data instead of fine-tuning parameters to ensure good segmentations. Doctor of Philosophy (SCE) 2008-09-17T09:03:24Z 2008-09-17T09:03:24Z 2003 2003 Thesis http://hdl.handle.net/10356/2454 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Tan, Choong Leong. Bayesian segmentation and restoration of magnetic resonance brain images |
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My objective in this research is to develop and extend existing image restora-tion techniques by introducing more powerful image models for MR images. The approach shall also be automated, data-driven, and require very minimal inter-ference from users so that neurologists can concerntrate on their job of analysing the data instead of fine-tuning parameters to ensure good segmentations. |
author2 |
Rajapakse, Jagath Chandana |
author_facet |
Rajapakse, Jagath Chandana Tan, Choong Leong. |
format |
Theses and Dissertations |
author |
Tan, Choong Leong. |
author_sort |
Tan, Choong Leong. |
title |
Bayesian segmentation and restoration of magnetic resonance brain images |
title_short |
Bayesian segmentation and restoration of magnetic resonance brain images |
title_full |
Bayesian segmentation and restoration of magnetic resonance brain images |
title_fullStr |
Bayesian segmentation and restoration of magnetic resonance brain images |
title_full_unstemmed |
Bayesian segmentation and restoration of magnetic resonance brain images |
title_sort |
bayesian segmentation and restoration of magnetic resonance brain images |
publishDate |
2008 |
url |
http://hdl.handle.net/10356/2454 |
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1759855645714022400 |