Automatic Robotic-Assisted Diffuse Reflectance Spectroscopy Scanning System

TL;DR

A robotic system to facilitate autonomous DRS scanning with hybrid visual servoing control is proposed and results show that the system can accurately execute the scanning command and acquire consistent DRS spectra with comparable results to the manual collection.

Abstract

Diffuse Reflectance Spectroscopy (DRS) is a well-established optical technique for tissue composition assessment which has been clinically evaluated for tumour detection to ensure the complete removal of cancerous tissue. While point-wise assessment has many potential applications, incorporating automated large-area scanning would enable holistic tissue sampling with higher consistency. We propose a robotic system to facilitate autonomous DRS scanning with hybrid visual servoing control. A specially designed height compensation module enables precise contact condition control. The evaluation results show that the system can accurately execute the scanning command and acquire consistent DRS spectra with comparable results to the manual collection, which is the current gold standard protocol. Integrating the proposed system into surgery lays the groundwork for autonomous intra-operative DRS tissue assessment with high reliability and repeatability. This could reduce the need for manual scanning by the surgeon while ensuring complete tumor removal in clinical practice.

Figures (8)

• Figure 1: Overview of the automatic DRS sampling system: previous DRS sampling relies on manual operation to position the DRS probe. This proposed system utilised the visual servoing module and contact height compensator to the robot to automatically position the probe. Two cameras capture views from different scales as feedback to the system.
• Figure 2: DRS automatic system: The left top is a zoomed view of a third-person camera image showing two image features: probe tip and illuminated area centre (also named as light centre), and a target point represented by a marker. The bottom left image illustrates the two stages of a DRS sampling procedure: the approach stage and the scanning stage. The right section is a diagram of the overall control. The system takes images from both cameras to extract the current visual state using two pairs of features and probe contact height. The visual servoing generates the motion to execute the scanning trajectory while tracking the target contact height. The resulting action drives the robot to sample DRS on the tissue surface.
• Figure 3: Example of wrist grey-scale camera images at different contact height. The width of the black background view in the camera view was $67\,\text{mm}$ when making contact at $0\,\text{mm}$.
• Figure 4: Visualising the evaluation results of height estimator neural network on testing dataset of horizontal movement on live phantom (10 trials) and lamb liver (30 trials). The range of $\pm5\,\text{mm}$ from the ground truth value is marked by green lines. Different trials are marked with different colors.
• Figure 5: 3D trajectory of approach to initial sampling point on a lamb liver sample. Positions are plotted by fixing target position at zero marked with a horizontal line.