Time-domain feature extraction for target-specificity in Photoacoustic Remote Sensing Microscopy

TL;DR

This paper introduces a novel clustering method for extracting time-domain features from Photoacoustic Remote Sensing microscopy signals, enabling target-specific tissue labeling and detailed visualization of tissue components.

Contribution

A new clustering technique for time-domain feature extraction in PARS microscopy that reveals biomolecular properties and enables virtual tissue labeling.

Findings

Successfully distinguished white and gray matter in murine brain tissue.

Produced colorized tissue visualizations highlighting specific structures.

Demonstrated potential for label-free, target-specific tissue analysis.

Abstract

Photoacoustic Remote Sensing (PARS) microscopy is an emerging label-free optical absorption imaging modality. PARS operates by capturing nanosecond-scale optical perturbations generated by photoacoustic pressures. These time-domain (TD) modulations are usually projected by amplitude to determine absorption magnitude. However, significant information on the target's material properties is contained within the TD signals. This work proposes a novel clustering method to learn TD features which relate to underlying biomolecule characteristics. This technique identifies features related to constituent biomolecules, enabling single-acquisition virtual tissue labelling. Colorized visualizations of tissue are produced, highlighting specific tissue components. This is demonstrated on freshly resected murine brain tissue, clearly discerning structures including myelinated and unmyelinated neurons (white and gray matter) and nuclear structures.