共焦
拉曼光谱
共焦显微镜
显微镜
拉曼显微镜
材料科学
生物医学工程
拉曼散射
病理
分辨率(逻辑)
光学
人工智能
计算机科学
医学
物理
作者
Jingchao Xing,Dong-Ryoung Lee,Jin Won Kim,Hongki Yoo
标识
DOI:10.1002/jbio.202200243
摘要
Confocal Raman microscopy is a useful tool to observe composition and constitution of label-free samples at high spatial resolution. However, accurate characterization of microstructure of tissue and its application in diagnostic imaging are challenging due to weak Raman scattering signal and complex chemical composition of tissue. We have developed a method to improve imaging speed, diffraction efficiency, and spectral resolution of confocal Raman microscopy. In addition to the novel imaging technique, the machine learning method enables confocal Raman microscopy to visualize accurate histology of tissue sections. Here, we have demonstrated the performance of the proposed method by measuring histological classification of atherosclerotic arteries and compared the histological confocal Raman images with the conventional staining method. Our new confocal Raman microscopy enables us to comprehend the structure and biochemical composition of tissue and diagnose the buildup of atherosclerotic plaques in the arterial wall without labeling.
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