SignificanceFluorescently guided minimally invasive surgery is improving patient outcomes and disease-free survival, but biomarker variability hinders complete tumor resection with single molecular probes. To overcome this, we developed a bioinspired endoscopic system that images multiple tumor-targeted probes, quantifies volumetric ratios in cancer models, and detects tumors in ex vivo…

SignificanceFluorescence-guided surgery (FGS) provides specific real-time visualization of tumors, but intensity-based measurement of fluorescence is prone to errors. Multispectral imaging (MSI) in the short-wave infrared (SWIR) has the potential to improve tumor delineation by enabling machine-learning classification of pixels based on their spectral characteristics.AimDetermine whether MSI can…

PurposeThe aim of this work is the development and characterization of a model observer (MO) based on convolutional neural networks (CNNs), trained to mimic human observers in image evaluation in terms of detection and localization of low-contrast objects in CT scans acquired on a reference phantom. The final goal is automatic image quality evaluation and CT protocol optimization to fulfill the…