Multimodal Optical Imaging Platform for Quantitative Burn Assessment

TL;DR

This paper introduces a portable multimodal optical imaging system combining hyperspectral and laser speckle contrast imaging to objectively assess burn severity by analyzing tissue biochemical and microvascular features, suitable for field use.

Contribution

The work develops a compact, low-SWaP device integrating novel deep-tissue parameters and unsupervised learning for accurate burn assessment in challenging environments.

Findings

Validated deep-tissue parameters improve burn tissue separation.

Unsupervised spectral analysis correlates well with histology.

Device demonstrates potential for rapid, objective burn evaluation.

Abstract

Accurate assessment of burn severity at injury onset remains a major clinical challenge due to the lack of objective methods for detecting subsurface tissue damage. This limitation is critical in battlefield and mass-casualty settings, where rapid and reliable evaluation of burn depth is essential for triage and surgical decision-making. We present a multimodal optical imaging framework that establishes the foundation for a compact, low-size, weight, and power (low-SWaP) field-deployable device for quantitative burn assessment. The system integrates broadband hyperspectral imaging (VSWIR, 400 -- 2100 nm) with laser speckle contrast imaging to jointly evaluate biochemical composition and microvascular perfusion. Using short-wave infrared (SWIR, >1000 nm) wavelengths, we developed and validated novel deep-tissue parameters linked to water, lipid, and collagen absorption features that enhance burn-tissue separability and burn severity classification. We implemented and validated unsupervised learning methods for spectral feature extraction, band down-selection, and clustering against histology, establishing a foundation for a rugged, data-driven device for early quantitative burn evaluation in austere environments.