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Colour differences between healthy and diseased tissue in thegastrointestinal tract are detected visually by clinicians during white lightendoscopy (WLE); however, the earliest signs of disease are often just aslightly different shade of pink compared to healthy tissue. Here, we proposeto target alternative colours for imaging to improve contrast using custommultispectral filter arrays (MSFAs) that could be deployed in an endoscopicchip-on-tip configuration. Using an open-source toolbox, Opti-MSFA, we examinedthe optimal design of MSFAs for early cancer detection in the gastrointestinaltract. The toolbox was first extended to use additional classification models(k-Nearest Neighbour, Support Vector Machine, and Spectral Angle Mapper). Usinginput spectral data from published clinical trials examining the oesophagus andcolon, we optimised the design of MSFAs with 3 to 9 different bands. Weexamined the variation of the spectral and spatial classification accuracy as afunction of number of bands. The MSFA designs have high classificationaccuracies, suggesting that future implementation in endoscopy hardware couldpotentially enable improved early detection of disease in the gastrointestinaltract during routine screening and surveillance. Optimal MSFA configurationscan achieve similar classification accuracies as the full spectral data in animplementation that could be realised in far simpler hardware. The reducednumber of spectral bands could enable future deployment of multispectralimaging in an endoscopic chip-on-tip configuration.

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