Multispectral Retinal Imaging and Mapping of Naturally Occurring Fluorophore and Chromophore Distributions in Health and Early Pathology

这项提案的总体目标是将健壮的自动化多光谱图像分析方法与多光谱视网膜反射和自体荧光成像相结合，以提供视网膜内自然存在的荧光团和生色团分布的定量地图。所得到的高分辨率多组分分子图将用于更好地了解正常视网膜老化和早期视网膜疾病进展中的分子事件。任务：-优化自动图像分析方法生成的分子图像图的质量，这些图像来自使用标准眼底相机中的特殊滤光片组获得的不同多光谱自发荧光和反射图像集。-应用光谱线性分离模型来提取纯亚像素光谱特征以获得临床上重要的多个内源性分子物种的局部浓度的变化-基于降维算法开发光谱分类方案以对局部细胞功能和病理进行分类-开发用于稀疏表示可再现特征的局部支持的多尺度(小波)表示系统，以便超时跟踪变化，特别是对于100微米量级的不同类别的早期病理损伤。

0854233CzajaThe overall objective of this proposal is to integrate robust automated multispectral image analysis methods with multispectral retinal reflectance and autofluorescence imaging to provide quantitative maps of naturally occurring fluorophores and chromophore distri-butions within the retina. The resulting high-resolution multi-component molecular maps would be applied to better understand molecular events in normal retinal aging and in early retinal disease progression.Tasks:- To optimize the quality of molecular image maps generated by automated imageanalysis methods from different multispectral sets of autofluorescence and reflectance images obtained using special filter sets in standard fundus cameras. Envisioned as an iterative process of refinement of filters, imaging protocols and analysis tools.- To apply spectral linear demixing models for extraction of pure subpixel spectral signatures to obtain clinically important changes in local concentrations of multiple endogenous molecular species- To develop spectral classification schemes based on dimension reduction algorithms to classify local cellular function and pathology- To develop locally supported multi-scale (wavelet) representation systems for sparse representation of reproducible features in order to follow changes overtime, particularly for different classes of early pathologic lesions on the order of 100 microns.