Fisher-Information-Driven Adaptive Acquisition for Photon-Efficient FLIM: A Dual-Implementation Framework for TCSPC and Programmable Time-Gating

TL;DR

This paper introduces a Fisher-information-based framework for optimizing photon-efficient FLIM imaging, improving sampling strategies under fixed photon budgets and enabling adaptive hardware-compatible acquisition methods.

Contribution

It develops a novel FI-based design approach for FLIM that accounts for nuisance parameters and enables adaptive, hardware-feasible sampling strategies without hardware changes.

Findings

FI-driven designs outperform uniform sampling in photon efficiency.

Nuisance-aware planning provides more stable gains under model mismatch.

Monte Carlo simulations confirm reduced estimator variance with optimized sampling.

Abstract

We present a Fisher-information (FI) framework for photon-efficient fluorescence lifetime imaging microscopy (FLIM) that treats temporal sampling as a controllable design variable under a fixed photon (dose) budget. Starting from a Poisson photon-counting model for bi-exponential fluorescence decays convolved with a finite instrument response function (IRF) and including additive background, we derive FI for both time-binned TCSPC histograms and programmable time-gated acquisitions. To ensure robustness when nuisance parameters such as IRF width, temporal offset, and background level are uncertain, we compute an effective FI using a Schur-complement marginalization and select hardware-feasible temporal designs by maximizing D-optimal criteria over candidate libraries. Across instrument-agnostic simulations spanning IRF broadening and increasing background fractions, FI-driven temporal designs consistently improve photon efficiency relative to uniform sampling, while nuisance-aware planning yields more stable gains under mismatch than naive optimization. Monte Carlo studies with maximum-likelihood estimation confirm that higher effective FI translates into reduced estimator variance and improved parametric map quality at fixed photon budgets. Finally, we map the same FI core to two practical deployment pathways: adaptive re-binning for TCSPC FLIM and adaptive gate placement/width selection for time-gated FLIM, enabling information-theoretic acquisition without hardware modification.