Code and data for: Decoupling channel count from field-of-view and spatial resolution in single-sensor imaging systems for fluorescence image-guided surgery

Significance Near-infrared fluorescence image-guided surgery is often thought of as a spectral imaging problem where the channel count is the critical parameter, but it should also be thought of as a multiscale imaging problem where the field-of-view and spatial resolution are similarly important. Aim Conventional imaging systems based on division-of-focal-plane architectures suffer from a strict relationship between the channel count on one hand and the field-of-view and spatial resolution on the other, but bioinspired imaging systems that combine stacked photodiode image sensors and long-pass/short-pass filter arrays offer a weaker tradeoff. Approach In this paper, we explore how the relevant changes to the image sensor and associated image processing routines affect image fidelity during image-guided surgeries for tumor removal in an animal model of breast cancer and nodal mapping in women with breast cancer. Results We demonstrate that a transition from a conventional imaging system to a bioinspired one, along with optimization of the image processing routines, yields improvements in multiple measures of spectral and textural rendition relevant to surgical decision-making. Conclusions These results call for a critical examination of the devices and algorithms that underpin image-guided surgery to ensure that surgeons receive high-quality guidance and patients receive high-quality outcomes as these technologies enter clinical practice. Methods The steps used to collect and process the data in this dataset have been documented in the associated manuscript.