Visualization of quantitative lipid distribution in mouse liver through near-infrared hyperspectral imaging

KYOHEI OKUBO, YUICHI KITAGAWA, NAOKI HOSOKAWA, MASAKAZU UMEZAWA, MASAO KAMIMURA, TOMONORI KAMIYA, NAOKO OHTANI, KOHEI SOGA

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)823-835
Number of pages13
JournalBiomedical Optics Express
Volume12
Issue number2
DOIs
Publication statusPublished - 2021

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