Accurate quantification of fluorescence signals in three-dimensional (3D) microscopy is often hindered by axial- and radial-position-dependent attenuation, limiting reliable measurements in live biological specimens. Here, we present a data-driven statistical correction model that compensates for signal loss arising from axial- and radial-position in 3D time-lapse imaging of Caenorhabditis elegans embryos. Our framework incorporates axial position (imaging depth, z), radial position (distance from the center of the field of view, r), together with cell cycle progression, to recover cell-specific fluorescence intensities independent of axial- and radial-positions. By leveraging repeated observations of biologically comparable states, the model infers attenuation directly from the data without requiring external calibration. Notably, the sign of the inferred radial-position-dependence in biological specimens was opposite to that observed in homogeneous fluorescent reference samples, underscoring the value of specimen-specific, data-driven correction. Validation using histone-tagged fluorescent proteins demonstrated that the method effectively removes geometric bias in nuclear fluorescence signals, enabling consistent quantification across cells and embryos. This approach provides a robust and generalizable solution for correcting intensity attenuation in volumetric microscopy datasets, thereby enabling more accurate and reproducible quantitative analyses in live imaging studies.
Ichihara, S., Akaho, S., Kuriki, S., Otomo, K., Nemoto, T., Kimura, A.
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