拉曼光谱
尿路上皮
成像光谱学
相位成像
材料科学
生物医学工程
高光谱成像
定量分析(化学)
光谱学
人工智能
相(物质)
显微镜
病理
计算机科学
光学
化学
医学
膀胱
内科学
物理
色谱法
量子力学
有机化学
作者
Almog Taieb,Garry Berkovic,Miki Haifler,Ori Cheshnovsky,Natan T. Shaked
标识
DOI:10.1002/jbio.202200009
摘要
We present a multimodal label-free optical measurement approach for analyzing sliced tissue biopsies by a unique combination of quantitative phase imaging and localized Raman spectroscopy. First, label-free quantitative phase imaging of the entire unstained tissue slice is performed using automated scanning. Then, pixel-wise segmentation of the tissue layers is performed by a kernelled structural support vector machine based on Haralick texture features, which are extracted from the quantitative phase profile, and used to find the best locations for performing the label-free localized Raman measurements. We use this multimodal label-free measurement approach for segmenting the urothelium in benign and malignant bladder cancer tissues by quantitative phase imaging, followed by location-guided Raman spectroscopy measurements. We then use sparse multinomial logistic regression (SMLR) on the Raman spectroscopy measurements to classify the tissue types, demonstrating that the prior segmentation of the urothelium done by label-free quantitative phase imaging improves the Raman spectra classification accuracy from 85.7% to 94.7%.
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