| Compressive hyperspectral time-resolved wide-field fluorescence lifetime imaging Q Pian, R Yao, N Sinsuebphon, X Intes Nature photonics 11 (7), 411-414, 2017 | 151 | 2017 |
| Fast fit-free analysis of fluorescence lifetime imaging via deep learning JT Smith, R Yao, N Sinsuebphon, A Rudkouskaya, N Un, J Mazurkiewicz, ... Proceedings of the national academy of sciences 116 (48), 24019-24030, 2019 | 122 | 2019 |
| Net-FLICS: fast quantitative wide-field fluorescence lifetime imaging with compressed sensing–a deep learning approach R Yao, M Ochoa, P Yan, X Intes Light: science & applications 8 (1), 26, 2019 | 83 | 2019 |
| Hyperspectral time-resolved wide-field fluorescence molecular tomography based on structured light and single-pixel detection Q Pian, R Yao, L Zhao, X Intes Optics letters 40 (3), 431-434, 2015 | 80 | 2015 |
| Generalized mesh-based Monte Carlo for wide-field illumination and detection via mesh retessellation R Yao, X Intes, Q Fang Biomedical optics express 7 (1), 171-184, 2016 | 78 | 2016 |
| Direct approach to compute Jacobians for diffuse optical tomography using perturbation Monte Carlo-based photon “replay” R Yao, X Intes, Q Fang Biomedical optics express 9 (10), 4588-4603, 2018 | 63 | 2018 |
| Assessing patterns for compressive fluorescence lifetime imaging M Ochoa, Q Pian, R Yao, N Ducros, X Intes Optics letters 43 (18), 4370-4373, 2018 | 33 | 2018 |
| Wide-field fluorescence molecular tomography with compressive sensing based preconditioning R Yao, Q Pian, X Intes Biomedical optics express 6 (12), 4887-4898, 2015 | 33 | 2015 |
| High compression deep learning based single-pixel hyperspectral macroscopic fluorescence lifetime imaging in vivo M Ochoa, A Rudkouskaya, R Yao, P Yan, M Barroso, X Intes Biomedical Optics Express 11 (10), 5401-5424, 2020 | 25 | 2020 |
| Hyperspectral wide-field time domain single-pixel diffuse optical tomography platform Q Pian, R Yao, X Intes Biomedical Optics Express 9 (12), 6258-6272, 2018 | 20 | 2018 |
| Improving mesoscopic fluorescence molecular tomography via preconditioning and regularization F Yang, R Yao, MS Ozturk, D Faulkner, Q Qu, X Intes Biomedical Optics Express 9 (6), 2765-2778, 2018 | 18 | 2018 |
| Deep compressive macroscopic fluorescence lifetime imaging R Yao, M Ochoa, X Intes, P Yan 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 12 | 2018 |
| Improving mesoscopic fluorescence molecular tomography through data reduction F Yang, MS Ozturk, R Yao, X Intes Biomedical Optics Express 8 (8), 3868-3881, 2017 | 10 | 2017 |
| Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via “photon sharing” S Yan, R Yao, X Intes, Q Fang Optics letters 45 (10), 2842-2845, 2020 | 9 | 2020 |
| Accelerating vasculature imaging in tumor using mesoscopic fluorescence molecular tomography via a hybrid reconstruction strategy F Yang, X Gong, D Faulkner, S Gao, R Yao, Y Zhang, X Intes Biochemical and biophysical research communications 562, 29-35, 2021 | 8 | 2021 |
| Time-resolved hyperspectral single-pixel camera implementation for compressive wide-field fluorescence lifetime imaging Q Pian, R Yao, X Intes Multimodal Biomedical Imaging XI 9701, 150-155, 2016 | 8 | 2016 |
| System configuration optimization for mesoscopic fluorescence molecular tomography F Yang, D Faulkner, R Yao, MS Ozturk, Q Qu, X Intes Biomedical Optics Express 10 (11), 5660-5674, 2019 | 7 | 2019 |
| Hyperspectral compressive single-pixel imager for fluorescence lifetime sensing Q Pian, R Yao, N Sinsuebphon, X Intes Optical Tomography and Spectroscopy, OTu2C. 7, 2016 | 7 | 2016 |
| A rapid approach to build Jacobians for optical tomography via Monte Carlo method and photon “replay” R Yao, X Intes, Q Fang Bio-Optics: Design and Application, BoW3A. 3, 2017 | 6 | 2017 |
| Ultra-fast fit-free analysis of complex fluorescence lifetime imaging via deep learning JT Smith, R Yao, N Sinsuebphon, A Rudkouskaya, J Mazurkiewicz, ... bioRxiv, 523928, 2019 | 4 | 2019 |
Intes XavierProf - Rensselaer Polytechnic InstituteGeverifieerd e-mailadres voor rpi.edu
