Review of Confocal Fluorescence Endomicroscopy for Cancer Detection

Selected Topics in Quantum Electronics, IEEE Journal of(2012)

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摘要
The cancer burden is increasing worldwide and there is a need to develop new technologies for cancer diagnosis. Confocal laser endomicroscopy (CLE) is a minimally invasive optical technique that enables in vivo confocal imaging of tissue structures. With the use of fluorescent dyes, the technique allows confocal fluorescence endomicroscopy of tissue from surface to subsurface layers. CLE has been applied to the surveillance and diagnosis of cancer in numerous clinical studies recently, and also holds potential for optical and guided biopsy procedures. The first part of this mini review is focused on the application of CLE for cancer detection and surveillance. The second part is focused on the application of CLE to imaging of the oral cavity. We have previously demonstrated the potential of CLE for diagnostic imaging of oral cavity lesions. To move toward real-time 3-D imaging, we interfaced an endomicroscope to an embedded computing system. The prototype system is capable of automated image acquisition and real-time volume rendering. Rendering results provide topographical and depth information. Our aim is to achieve a real-time 3-D fluorescence imaging system that can be used for diagnostic imaging and guided biopsy procedures of oral cavity lesions in a clinical setting.
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关键词
biological tissues,biomedical optical imaging,cancer,dyes,endoscopes,fluorescence spectroscopy,laser applications in medicine,medical image processing,optical microscopy,cle,automated image acquisition,cancer detection,cancer diagnosis,cancer surveillance,confocal fluorescence endomicroscopy,confocal laser endomicroscopy,depth information,diagnostic imaging,embedded computing system,fluorescent dyes,guided biopsy procedures,in vivo confocal imaging,minimally invasive optical technique,oral cavity imaging,oral cavity lesions,real time volume rendering,tissue structures,topographical information,fluorescence,image processing,laser biomedical applications,real-time systems,embedded computing,fluorescence imaging,real time systems,real time,volume rendering
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