| 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 |
| Segmentation of breast ultrasound images based on active contours using neutrosophic theory M Lotfollahi, M Gity, JY Ye, A Mahlooji Far Journal of Medical Ultrasonics 45, 205-212, 2018 | 43 | 2018 |
| 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 |
| 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 |
| 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 |
| 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 |
| Digital Staining of High-Resolution Ftir Spectroscopic Images M Lotfollahi, D Daeinejad, S Berisha, D Mayerich 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018 | 1 | 2018 |
| Reconstructing High-Definition Infrared Spectroscopic Images Using Adaptive Sampling and Deep Learning M Lotfollahi | | 2020 |
