Document Detail

An automated template-based adaptive threshold approach for measuring ventricular volume enlargement in mouse brain MR microscopy.
MedLine Citation:
PMID:  23140374     Owner:  NLM     Status:  In-Data-Review    
Mouse models for human diseases play an important role in developing therapeutic measures and understanding disease development and mechanisms. Ventricular enlargement is an objective and sensitive biomarker of neuropathological change associated with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Thus, imaging based volumetric measures of mouse brain ventricle can be used as a biomarker for detecting and monitoring pathology. However, till now most mouse ventricular segmentation is still based on manual tracing, and current region of interests (ROIs) labelling approaches on mouse brain don't work well on small brain structure like ventricle. In this paper, an automated template-based method was developed to evaluate for the identification of a ventricular ROIs in mouse brain imaging studies. Monte Carlo simulation was applied to evaluate the efficiency of this approach in detecting computer-simulated ventricle in laboratory mice. The method demonstrated a satisfactory performance with consistent high correlations between the detected and simulated volume changes. This approach can be used to investigate the ventricular volume changing in transgenic mice and other putative animal models of AD.
Lan Lin; Shuicai Wu
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of microscopy     Volume:  248     ISSN:  1365-2818     ISO Abbreviation:  J Microsc     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-11-12     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0204522     Medline TA:  J Microsc     Country:  England    
Other Details:
Languages:  eng     Pagination:  260-5     Citation Subset:  IM    
Copyright Information:
© 2012 The Authors Journal of Microscopy © 2012 Royal Microscopical Society.
Biomedical Research Center, College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100022, China.
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