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.