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High-resolution large-scale mosaic imaging using multiphoton microscopy to characterize transgenic mouse models of human neurological disorders.
- Source :
-
Neuroinformatics [Neuroinformatics] 2006 Winter; Vol. 4 (1), pp. 65-80. - Publication Year :
- 2006
-
Abstract
- The thorough characterization of transgenic mouse models of human central nervous system diseases is a necessary step in realizing the full benefit of using animal models to investigate disease processes and potential therapeutics. Because of the labor- and resource-intensive nature of high-resolution imaging, detailed investigation of possible structural or biochemical alterations in brain sections has typically focused on specific regions of interest as determined by the researcher a priori. For example, Parkinson's disease researchers often focus imaging on regions of the brain expected to exhibit pathology such as the substantia nigra and striatum. Because of limitations in acquiring and storing high-resolution imaging data, additional data contained in the specimen is not usually acquired or disseminated/reported to the research community. Here we present a method of imaging large regions of brain at close to the resolution limit of light microscopy using a mosaic imaging technique in conjunction with multiphoton microscopy. These maps are being used to characterize several genetically modified animal models of neurological disease by filling the information "gap" among techniques such as magnetic resonance imaging and electron microscopic analysis.
- Subjects :
- Animals
Brain Mapping instrumentation
Computer Communication Networks trends
Disease Models, Animal
Humans
Image Processing, Computer-Assisted instrumentation
Image Processing, Computer-Assisted trends
Medical Illustration
Mice
Mice, Transgenic
Microscopy, Fluorescence, Multiphoton trends
Software
User-Computer Interface
Brain pathology
Brain Mapping methods
Image Processing, Computer-Assisted methods
Microscopy, Fluorescence, Multiphoton methods
Nervous System Diseases pathology
Subjects
Details
- Language :
- English
- ISSN :
- 1539-2791
- Volume :
- 4
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Neuroinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 16595859
- Full Text :
- https://doi.org/10.1385/NI:4:1:65