Xavier Intes

This paper introduces a deep learning method called AUTO-FLI for 3D fluorescence lifetime imaging in deep tissues, showing it can accurately reconstruct intensity and lifetime data in scattering media.

This paper introduces a real-time fluorescence lifetime imaging method using single-snapshot acquisitions, demonstrating its application in biomedical scenarios from microscopic to macroscale.

This paper introduces HSF-FLI, a method to isolate subsurface fluorescence signals in MFLI, validated in vivo and ex vivo with mouse tumor models.

This study uses fluorescence lifetime imaging to quantify TZM-HER2 binding and distribution in tumors with varying microenvironments, showing differences in drug delivery efficacy between cancer types.

This study evaluates contrast agents for photon-counting micro-CT in tumor xenografts, finding that Exitrone Nano 12000 provides better vasculature enhancement and consistency compared to ISOVUE-370.

This study examines how efference information flow during skill acquisition interacts with medical simulation technology, showing skill level and simulation type affect brain network dynamics.

The paper compares interhemispheric functional connectivity in the primary motor cortex between physical and virtual surgical simulators using fNIRS and finds distinct connectivity patterns.

This paper introduces an optical neuroimaging method to objectively classify bimanual motor skill expertise, showing it outperforms current metrics in surgical certification.