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MULTIMODAL SPECTROSCOPY PROBE DEVELOPMENT

MULTIMODAL SPECTROSCOPY PROBE DEVELOPMENT
多模态光谱探头开发
批准号:
7722788
负责人:
OBRAD SCEPANOVIC
金额:
$3.81万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-06-01 至 2009-05-31

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项目成果

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中文摘要
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英文摘要
This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We are investigating the utility of combining diagnostic information from reflectance and fluorescence to that obtained by Raman spectroscopy  termed multimodal spectroscopy (MMS) - to diagnose atherosclerosis and breast cancer. As a result, a single spectral probe is being developed to be used with all three modalities. The combined probe would take excitation light from existing reflectance, fluorescence, and Raman sources and deliver to and collect the light from the same tissue location. The combined probe is designed to be capable of delivering and collecting light in the 300-1000 nm spectral range. Based on the in vivo Raman probe that has been successful used in the surgical theatre, the combined probe will enable the coupling of multiple sources into its single excitation fiber, incorporate excitation and emission filters with specially designed optical coatings to suppress fiber background and enable efficient extraction of the desired signal. Collection fibers would be split up and be directed to two spectrograph/CCD modules of the clinical MMS instrument for spectral analysis and parameter extraction.
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会议论文
ESTIMATION AND ERROR ANALYSIS IN MULTIMODAL SPECTROSCOPY
OPTICAL FIBER PROBE FOR BIOMEDICAL RAMAN SPECTROSCOPY
DETECTION OF VULNERABLE PLAQUES USING RAMAN, FLUORESCENCE AND REFLECTANCE SPECT
OPTICAL FIBER PROBE FOR BIOMEDICAL RAMAN SPECTROSCOPY
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海外基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data