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Visualization of quantitative lipid distribution in mouse liver through near-infrared hyperspectral imaging
Biomedical Optics Express ( IF 3.4 ) Pub Date : 2021-01-12 , DOI: 10.1364/boe.413712
Kyohei Okubo 1 , Yuichi Kitagawa 1 , Naoki Hosokawa 1 , Masakazu Umezawa 1 , Masao Kamimura 1 , Tomonori Kamiya 2 , Naoko Ohtani 2 , Kohei Soga 1
Affiliation  

Lipid distribution in the liver provides crucial information for diagnosing the severity of fatty liver and fatty liver-associated liver cancer. Therefore, a noninvasive, label-free, and quantitative modality is eagerly anticipated. We report near-infrared hyperspectral imaging for the quantitative visualization of lipid content in mouse liver based on partial least square regression (PLSR) and support vector regression (SVR). Analysis results indicate that SVR with standard normal variate pretreatment outperforms PLSR by achieving better root mean square error (15.3 mg/g) and higher determination coefficient (0.97). The quantitative mapping of lipid content in the mouse liver is realized using SVR.

中文翻译:

通过近红外高光谱成像可视化小鼠肝脏中定量脂质分布

肝脏中的脂质分布为诊断脂肪肝和脂肪肝相关肝癌的严重程度提供了重要信息。因此,人们迫切期待一种无创、无标记、定量的方式。我们报告了基于偏最小二乘回归(PLSR)和支持向量回归(SVR)的近红外高光谱成像,用于定量可视化小鼠肝脏中的脂质含量。分析结果表明,采用标准正态变量预处理的 SVR 优于 PLSR,具有更好的均方根误差 (15.3 mg/g) 和更高的判定系数 (0.97)。使用SVR实现了小鼠肝脏中脂质含量的定量图谱。
更新日期:2021-02-01
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