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In-Vivo Microvasculature Visualization Using Hyperspectral Imaging

机译:使用高光谱成像的体内微脉管系统可视化

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We describe a new noninvasive microscopic near infrared reflectance hyperspectral imaging method for visualizing, in vivo, spatially distributed contributions of oxyhemoglobin perfusing the microvasculature within dermal tissue. Microscopic images of the dermis are acquired, generating a series of spectroscopic images formatted as a function of wavelength consisting of one spectral and two spatial dimensions; a hyperspectral image data cube. The data thus collected can be considered as a series of spatially resolved spectra. For data collection, images are acquired by a system consisting of a near infrared liquid crystal tunable filter (LCTF) and a Focal plane array detector (FPA) integrated with a microscope. The LCTF is continuously tunable over a useful near infrared spectral range (650-950 nm) with an average full width at half-height bandwidth of 6.78 nm. To provide high quantum efficiency without etaloning we utilized a back-illumination FPA with deep -depletion technology. A 30W halogen light source illuminates a dermal tissue area of approximately 18 mm in diameter. Reflected light from the dermal tissue is first passed through the microscope, the LCTF, and then imaged onto the FPA. The acquired hyperspectral data is deconvoluted using a multivariate least squares approach that requires at least two reference spectra, oxy- and deoxyhemoglobin. The resulting images are gray scale encoded to directly represent the varying spatial distributions of oxyhemoglobin contribution. As a proof of principle example, we examined a clinical model of vascular occlusion and reperfusion.
机译:我们描述了一种新的无创显微近红外反射高光谱成像方法,用于可视化氧合血红蛋白在体内渗透到皮肤组织内的微脉管系统中,在体内,空间分布上的贡献。获取真皮的显微图像,生成一系列光谱图像,这些光谱图像被格式化为波长的函数,该波长包括一个光谱和两个空间维度。高光谱图像数据立方体。如此收集的数据可以被认为是一系列空间分辨的光谱。对于数据收集,图像是通过由近红外液晶可调滤光片(LCTF)和与显微镜集成的焦平面阵列检测器(FPA)组成的系统获取的。 LCTF可在有用的近红外光谱范围(650-950 nm)上连续可调,半高带宽的平均全宽为6.78 nm。为了在没有标准具的情况下提供高量子效率,我们使用了具有深耗尽技术的背照式FPA。 30W卤素灯光源照亮直径约18毫米的真皮组织区域。来自真皮组织的反射光首先穿过显微镜LCTF,然后成像到FPA上。使用需要至少两个参考光谱(氧合和脱氧血红蛋白)的多元最小二乘法对获得的高光谱数据进行反卷积。生成的图像经过灰度编码,可以直接表示氧合血红蛋白贡献的变化空间分布。作为原理示例的证明,我们检查了血管闭塞和再灌注的临床模型。

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