A growing challenge currently faced by the biomedical community is to gain functional insights into the genomics of the nervous system in sufficient detail to understand human disease, derive novel therapies, and discover new drugs. Discovering changes in gene activity in localized cell populations of the brain under different experimental conditions can significantly expand the knowledge of how gene products interact as well as how they affect biological processes and human disease. One approach to assess changes in spatial gene expression is to register the datasets into a common domain - an atlas - in which experimental alterations can be assessed systematically. Increasing the accuracy of registration enables comparisons between even smaller functional features. The goal of this project is to develop a novel 3D atlas of the mouse brain and corresponding informatics tools that will lead to more powerful comparisons of gene expression image datasets.
The specific aims are: 1. Develop multimaterial volumetric subdivision mesh technology and construct a deformable adaptive resolution 3D atlas of the adult mouse brain. 2. Achieve interactive registration of the 3D atlas to volumetric datasets and validate accuracy of registration. 3. Assess the comparison capabilities of the 3D atlas using a set of experimental data collected to better understand the molecular mechanisms of the human genetic disorder Rett Syndrome.
This project will develop new software tools that will enable researchers to better understand the biological processes underlying human development and human diseases, potentially leading to new therapies. These tools include a new technique for digitally representing volume-based information that can improve comparisons between sets of data, a method for placing large-scale image data of gene activity in the mouse brain into this new representation, and the means to perform comparisons of this data at high resolution.
|Liu, Lu; Commean, Paul K; Hildebolt, Charles et al. (2013) Automated, foot-bone registration using subdivision-embedded atlases for spatial mapping of bone mineral density. J Digit Imaging 26:554-62|
|Le, Yen H; Kurkure, Uday; Paragios, Nikos et al. (2012) Similarity-based appearance-prior for fitting a subdivision mesh in gene expression images. Med Image Comput Comput Assist Interv 15:577-84|
|Kurkure, Uday; Le, Yen H; Paragios, Nikos et al. (2011) Landmark/Image-based Deformable Registration of Gene Expression Data. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit :1089-1096|
|Kindle, L M; Kakadiaris, I A; Ju, T et al. (2011) A semiautomated approach for artefact removal in serial tissue cryosections. J Microsc 241:200-6|
|Kurkure, Uday; Le, Yen H; Paragios, Nikos et al. (2011) Markov Random Field-based Fitting of a Subdivision-based Geometric Atlas. Proc IEEE Int Conf Comput Vis 2011:2540-2547|
|Enlow, Matthew A; Ju, Tao; Kakadiaris, Ioannis A et al. (2011) Lossless 3-D reconstruction and registration of semi-quantitative gene expression data in the mouse brain. Conf Proc IEEE Eng Med Biol Soc 2011:8086-9|
|Carson, James; Ju, Tao; Bello, Musodiq et al. (2010) Automated pipeline for atlas-based annotation of gene expression patterns: application to postnatal day 7 mouse brain. Methods 50:85-95|
|Ju, Tao; Carson, James; Liu, Lu et al. (2010) Subdivision meshes for organizing spatial biomedical data. Methods 50:70-6|