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- Title
- DEVELOPMENT AND EVALUATION OF MRI TEMPLATES OF THE MIITRA ATLAS
- Creator
- RIDWAN, ABDUR RAQUIB
- Date
- 2021
- Description
-
Digital human brain atlases play a pivotal role in conducting wide range of neuroimaging studies and are commonly used as references for...
Show moreDigital human brain atlases play a pivotal role in conducting wide range of neuroimaging studies and are commonly used as references for spatial normalization in voxel-wise analysis, region-of interest analyses, automated tissue-segmentation, functional connectivity analyses, etc. A brain atlas typically consists of MRI-based multi-modal templates and semantic labels delineating brain regions according to the characteristics of the underlying tissue. In recent times there has been a plethora of magnetic resonance imaging (MRI) studies on older adults without dementia to explore the role of brain characteristics associated with cognitive functions in old age with the ultimate goal to develop strategies for prevention of cognitive decline. Increasing the accuracy in terms of sensitivity and specificity of such neuroimaging studies require an atlas with a comprehensive set of high-quality templates representative of the brain characteristics typical of older adults and detailed labels accurately mapping brain regions of interest. However, such an atlas has not been constructed for older adults without dementia. Hence this thesis aims to build high quality MRI templates which are the cornerstone resources needed for the development of a comprehensive, high quality, multi-channel, longitudinal, probabilistic digital human brain atlas for older adults termed as Multi-channel Illinois Institute of Technology and Rush University Aging (MIITRA) atlas. This dissertation focuses on a) to develop and evaluate a high performing 1mm isotropic structural T1-weighted brain template, b) to investigate the development and evaluation of a spatio-temporally consistent longitudinal structural T1-weighted template of the older adult brain, c) to develop and evaluate an unbiased 0.5 mm isotropic super-resolved high resolution and detail-preserving structural T1 weighted template of the older adult brain, d) to develop an unbiased 0.5 mm super-resolved high resolution and detail-preserving structural PD weighted and T2-weighted template of the older adult brain, e) to investigate and provide future directions in the development of a 0.5 mm super-resolved high resolution DTI template of the older adult brain, and f) to construct a novel approach in the development of MRI templates using both space and frequency information of spatially normalized older adult data. The thesis based on the aforementioned foundational points was constructed as follows: Firstly, this thesis presents the development of a 1mm isotropic T1-weighted structural template of the older adult brain utilizing state of the art registration algorithm ANTs with parameters carefully optimized for older adults, in an iterative groupwise spatial normalization framework. The preprocessing steps were also thoroughly investigated to ensure high quality data. It was demonstrated through systematic comparison of this new template to several other standardized and study-specific T1-weighted templates that a) it exhibited high image sharpness, b) allowed for high spatial normalization accuracy and detection of smaller inter-group morphometric differences compared to other standardized templates, c) had similar performance to that of study-specific templates and d) was highly representative of the older adult brain. Secondly, with the acquired technical know-how from the aforementioned research findings a new method was introduced for the construction of a spatio-temporally consistent longitudinal template based on high quality cross-sectional older adult data from a large cohort. The new template was compared to templates generated with previously published methods in terms of spatio-temporal consistency and image quality and was shown to have superior performance. In addition, a novel approach was introduced for image quality enhancement of the longitudinal templates utilizing both space and frequency information. Thirdly, the thesis presents a method that involves a) thoroughly refining registration parameters, b) patch-based tissue-guided sparse-representation approach in a super-resolved unbiased minimum deformation space to construct and evaluate an unbiased 0.5 mm isotropic super-resolved high resolution and detail-preserving structural T1 weighted template of the older adult brain. This method accounts for misregistration specially in the cortical regions, ensuring sharp delineation of structures representative of the older adult brain. The new template developed using this approach maintained high anatomical consistency with sharp and detailed cortical features in the brain and exhibited higher image sharpness compared to other high-resolution standardized templates and allowed for high spatial normalization accuracy when used as a reference for normalization of older adult data. Additionally, this approach of template building was investigated on DTI tensors of older adult participants, and the constructed DTI template was shown to perform better than templates developed using the best approach currently present in the literature. Finally, the thesis presents the development of an unbiased 0.5 mm super-resolved high resolution and detail-preserving structural PD weighted and T2-weighted template of the older adult brain, from nonlocal super-resolution based upsampled PD and T2w older adult participant data, using this new template building approach.
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- Title
- FUNCTIONAL CONNECTIVITY LABELS FOR THE MULTICHANNEL IIT AND RUSH UNIVERSITY AGING (MIITRA) ATLAS
- Creator
- Badhon, Rashadul Hasan
- Date
- 2022
- Description
-
In the field of medical imaging, a brain atlas refers to a specific model of the brain of a population where different parts of the atlas...
Show moreIn the field of medical imaging, a brain atlas refers to a specific model of the brain of a population where different parts of the atlas correspond to different anatomical parts of the average brain of the population. A brain atlas is composed of MRI templates and semantic labels and is a crucial component of neuroscience for its critical role in facilitating spatial normalization, temporal characterization and automated segmentation for the purposes of voxel-wise, region of interest and network analyses. Building a brain atlas requires registering multi-dimensional brain datasets from a population into a reference space and, during the last decade, the advent of new technologies and computational modeling approaches has made it possible to build high-quality, detailed brain atlases. At the same time developments in data acquisition now allow the construction of comprehensive brain atlases containing a variety of information about the brain. The Multichannel Illinois Institute of Technology and Rush university Aging (MIITRA) atlas project is developing a high-quality comprehensive atlas of the older adult brain containing a multitude of templates and labels. These templates are constructed with state-of-the-art spatial normalization of high-quality data and as a result, they are characterized by higher image quality, are more representative of the brain of non-demented older adults and provide higher inter-subject spatial normalization accuracy of older adult data compared to other available templates. The methodology used in the development of the MIITRA templates facilitates the construction of accurate structural and connectivity labels. Functional connectivity MRI reveals sets of functionally connected brain regions, forming networks, by investigating synchronous fluctuations in MRI signal over time across these brain regions during rest. The purpose of this work was to generate functional connectivity labels for several brain networks in MIITRA space.
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- Title
- Development of Human Brain Atlas Resources
- Creator
- Qi, Xiaoxiao
- Date
- 2020
- Description
-
Digital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers,...
Show moreDigital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers, training data for machine learning algorithms, functional connectivity analysis and so on. A brain atlas typically consists of brain templates of different imaging modalities that are representative of individual brains under study in a standard atlas space and semantic labels that delineate brain regions according to the characteristics of the underlying tissue.The IIT Human Brain Atlas project has developed the state-of-the-art diffusion tensor imaging (DTI) template, high angular resolution diffusion imaging (HARDI) template, and anatomical templates for the young adult brain in a standardized space. The probabilistic maps of gray matter (GM) labels and tissue segmentations were also constructed based on the anatomical information of the atlas. This thesis introduced an enhanced T1-weighted template that were developed by combining information from both diffusion and anatomical data. The GM labels and tissue segmentation maps in the standardized space were also improved. Existing white matter (WM) atlases typically lack specificity in terms of brain connectivity. A new approach named regionconnect was developed in this work based on precalculated average healthy adult brain connectivity information stored in standard space in a fashion that allows fast retrieval and integration. This thesis first generated and evaluated the white matter connectome of the IIT Human Brain Atlas v.5.0. Next, the new white matter connectome was used to develop multi-layer, connectivity-based labels for each white matter voxel of the atlas, consistent with the fact that each voxel may contain axons from multiple connections. The regionconnect algorithm was then developed to rapidly integrate information contained in the multi-layer labels across voxels of a white matter region and to generate a list of the most probable connections traversing that region. The regionconnect algorithm as well as the white matter tractogram and connectome, multi-layer, connectivity-based labels, and associated resources developed for the IIT Human Brain Atlas v.5.0 in this work are available at www.nitrc.org/projects/iit. Furthermore, it was well established that use of a young adult atlas in studies of older adults is inappropriate due to the age-related characteristic changes of the brain, resulting in an increasing demand of digital brain atlases for the older adults. To fulfill this demand, a function of fiber orientation distribution (fODF) template that is representative of older adults was developed in a standardized atlas space for studies of white matter of older adult human brains, which built a solid foundation for the development of the white matter resources for the older adults human brain atlas.
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