Presentation Information

[10p-A13-8]Region-selective Raman Microspectroscopy for Molecular Spectral Tracking of Multicellular Samples

〇Takeru Sasaki1, Wataru Yamamoto1, Miho Mashima1, Ryosuke Oketani1, Kotaro Hiramatsu1 (1.Kyushu Univ.)

Keywords:

Deep Learning,Time-lapse Measurements,High-speed Raman Imaging

In this presentation, we report a region-selective Raman microspectroscopy method that combines deep-learning-based image recognition with local Raman spectroscopy to track molecular spectral changes in individual cells within a multicellular sample. Cell regions are extracted from bright-field images, and only the required regions are selectively measured, enabling efficient molecular spectral tracking. In addition to demonstrating accelerated analysis through bead identification, we performed 20-hour time-lapse measurements of 100 live cells with a temporal resolution of approximately 5 minutes and acquired molecular spectral changes associated with cell death.