Targeted Multispectral Filter Array Design for Endoscopic Cancer Detection in the Gastrointestinal Tract

TL;DR

This paper presents the design of custom multispectral filter arrays optimized for early gastrointestinal cancer detection, aiming to improve contrast and enable simpler, hardware-efficient endoscopic imaging.

Contribution

It introduces an open-source toolbox for designing multispectral filter arrays tailored for endoscopic cancer detection, extending models and optimizing configurations with fewer spectral bands.

Findings

High classification accuracy with optimized MSFA designs

Fewer spectral bands achieve similar accuracy to full spectral data

Potential for hardware simplification in endoscopic imaging

Abstract

Colour differences between healthy and diseased tissue in the gastrointestinal tract are detected visually by clinicians during white light endoscopy (WLE); however, the earliest signs of disease are often just a slightly different shade of pink compared to healthy tissue. Here, we propose to target alternative colours for imaging to improve contrast using custom multispectral filter arrays (MSFAs) that could be deployed in an endoscopic chip-on-tip configuration. Using an open-source toolbox, Opti-MSFA, we examined the optimal design of MSFAs for early cancer detection in the gastrointestinal tract. The toolbox was first extended to use additional classification models (k-Nearest Neighbour, Support Vector Machine, and Spectral Angle Mapper). Using input spectral data from published clinical trials examining the oesophagus and colon, we optimised the design of MSFAs with 3 to 9 different bands. We examined the variation of the spectral and spatial classification accuracy as a function of number of bands. The MSFA designs have high classification accuracies, suggesting that future implementation in endoscopy hardware could potentially enable improved early detection of disease in the gastrointestinal tract during routine screening and surveillance. Optimal MSFA configurations can achieve similar classification accuracies as the full spectral data in an implementation that could be realised in far simpler hardware. The reduced number of spectral bands could enable future deployment of multispectral imaging in an endoscopic chip-on-tip configuration.