Inference of Haemoglobin Concentration From Stereo RGB

TL;DR

This paper introduces a near real-time RGB-based method for estimating tissue haemoglobin concentration and oxygenation during surgery, leveraging stereo laparoscope images and constrained linear models with regularisation.

Contribution

It presents a novel, computationally efficient technique for intrinsic tissue measurement using only RGB stereo images, without hardware modifications.

Findings

Robust estimation of total haemoglobin achieved with Tikhonov regularisation.

Stereo RGB images enable accurate SO2 estimation in tissue.

Method validated on synthetic and in vivo porcine data.

Abstract

Multispectral imaging (MSI) can provide information about tissue oxygenation, perfusion and potentially function during surgery. In this paper we present a novel, near real-time technique for intrinsic measurements of total haemoglobin (THb) and blood oxygenation (SO2) in tissue using only RGB images from a stereo laparoscope. The high degree of spectral overlap between channels makes inference of haemoglobin concentration challenging, non-linear and under constrained. We decompose the problem into two constrained linear sub-problems and show that with Tikhonov regularisation the estimation significantly improves, giving robust estimation of the Thb. We demonstrate by using the co-registered stereo image data from two cameras it is possible to get robust SO2 estimation as well. Our method is closed from, providing computational efficiency even with multiple cameras. The method we present requires only spectral response calibration of each camera, without modification of existing laparoscopic imaging hardware. We validate our technique on synthetic data from Monte Carlo simulation % of light transport through soft tissue containing submerged blood vessels and further, in vivo, on a multispectral porcine data set.