| Deep learning for FTIR histology: leveraging spatial and spectral features with convolutional neural networks S Berisha, M Lotfollahi, J Jahanipour, I Gurcan, M Walsh, R Bhargava, ... Analyst 144 (5), 1642-1653, 2019 | 91 | 2019 |
| Iterative methods for image restoration S Berisha, JG Nagy Academic Press Library in Signal Processing 4, 193-247, 2014 | 73 | 2014 |
| Digital staining of high-definition Fourier transform infrared (FT-IR) images using deep learning M Lotfollahi, S Berisha, D Daeinejad, D Mayerich Applied spectroscopy 73 (5), 556-564, 2019 | 31 | 2019 |
| Measurement of Myocardial T1ρ with a Motion Corrected, Parametric Mapping Sequence in Humans S Berisha, J Han, M Shahid, Y Han, WRT Witschey PLoS One 11 (3), e0151144, 2016 | 25 | 2016 |
| Mitigating fringing in discrete frequency infrared imaging using time-delayed integration S Ran, S Berisha, R Mankar, WC Shih, D Mayerich Biomedical optics express 9 (2), 832-843, 2018 | 23 | 2018 |
| SIproc: an open-source biomedical data processing platform for large hyperspectral images S Berisha, S Chang, S Saki, D Daeinejad, Z He, R Mankar, D Mayerich Analyst 142 (8), 1350-1357, 2017 | 21 | 2017 |
| Bim-sim: Interactive simulation of broadband imaging using mie theory S Berisha, T Van Dijk, R Bhargava, PS Carney, D Mayerich Frontiers in physics 5, 5, 2017 | 19 | 2017 |
| Deblurring and sparse unmixing of hyperspectral images using multiple point spread functions S Berisha, JG Nagy, RJ Plemmons SIAM Journal on Scientific Computing 37 (5), S389-S406, 2015 | 13 | 2015 |
| Automated osteosclerosis grading of clinical biopsies using infrared spectroscopic imaging R Mankar, CE Bueso-Ramos, CC Yin, JE Hidalgo-Lopez, S Berisha, ... Analytical chemistry 92 (1), 749-757, 2019 | 10 | 2019 |
| Image classification using Gabor filters and machine learning S Berisha Wake Forest University, 2009 | 10 | 2009 |
| Restore tools: Iterative methods for image restoration, 2012 S Berisha, JG Nagy | 9 | |
| Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer CC Gajjela, M Brun, R Mankar, S Corvigno, N Kennedy, Y Zhong, J Liu, ... Analyst 148 (12), 2699-2708, 2023 | 8 | 2023 |
| Estimation of atmospheric PSF parameters for hyperspectral imaging S Berisha, JG Nagy, RJ Plemmons Numerical Linear Algebra with Applications 22 (5), 795-813, 2015 | 7 | 2015 |
| Deep learning for hyperspectral image analysis, Part I: Theory and algorithms S Berisha, FF Shahraki, D Mayerich, S Prasad Hyperspectral Image Analysis: Advances in Machine Learning and Signal …, 2020 | 5 | 2020 |
| Three-dimensional GPU-accelerated active contours for automated localization of cells in large images M Lotfollahi, S Berisha, L Saadatifard, L Montier, J Žiburkus, D Mayerich Plos one 14 (6), e0215843, 2019 | 4 | 2019 |
| Continuous adaptive radial sampling of k-space from real-time physiologic feedback in MRI F Contijoch, Y Han, M Hansen, P Kellman, E Gualtieri, M Elliott, S Berisha, ... Journal of Cardiovascular Magnetic Resonance 17 (Suppl 1), P37, 2015 | 3 | 2015 |
| Adaptive Compressive Sampling for Mid-Infrared Spectroscopic Imaging M Lotfollahi, N Tran, C Gajjela, S Berisha, Z Han, D Mayerich, R Reddy 2022 IEEE International Conference on Image Processing (ICIP), 2336-2340, 2022 | 2 | 2022 |
| Closed-loop control of k-space sampling via physiologic feedback for cine MRI F Contijoch, Y Han, S Kamesh Iyer, P Kellman, G Gualtieri, MA Elliott, ... PloS one 15 (12), e0244286, 2020 | 2 | 2020 |
| Deep learning for hyperspectral image analysis, part ii: Applications to remote sensing and biomedicine FF Shahraki, L Saadatifard, S Berisha, M Lotfollahi, D Mayerich, S Prasad Hyperspectral Image Analysis: Advances in Machine Learning and Signal …, 2020 | 2 | 2020 |
| BIM-sim: interactive simulation of broadband imaging using Mie theory S Berisha, T van Dijk, R Bhargava, PS Carney, D Mayerich Microscopy and Microanalysis 22 (S3), 1438-1439, 2016 | 2 | 2016 |
