David Le
Affiliations: | University of Illinois at Chicago, Chicago, IL, United States |
Area:
Bioengineering, Optics, Machine LearningGoogle:
"David Le"Mean distance: (not calculated yet)
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Publications
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| Le D, Abtahi M, Adejumo T, et al. (2023) Deep learning for artery-vein classification in optical coherence tomography angiography. Experimental Biology and Medicine (Maywood, N.J.). 15353702231181182 |
| Abtahi M, Le D, Ebrahimi B, et al. (2023) An open-source deep learning network AVA-Net for arterial-venous area segmentation in optical coherence tomography angiography. Communications Medicine. 3: 54 |
| Dadzie AK, Le D, Abtahi M, et al. (2023) Normalized Blood Flow Index in Optical Coherence Tomography Angiography Provides a Sensitive Biomarker of Early Diabetic Retinopathy. Translational Vision Science & Technology. 12: 3 |
| Le D, Dadzie A, Son T, et al. (2023) Comparative Analysis of OCT and OCT Angiography Characteristics in Early Diabetic Retinopathy. Retina (Philadelphia, Pa.) |
| Abtahi M, Le D, Lim JI, et al. (2022) MF-AV-Net: an open-source deep learning network with multimodal fusion options for artery-vein segmentation in OCT angiography. Biomedical Optics Express. 13: 4870-4888 |
| Le D, Son T, Lim JI, et al. (2022) Quantitative optical coherence tomography reveals rod photoreceptor degeneration in early diabetic retinopathy. Retina (Philadelphia, Pa.) |
| Adejumo T, Kim TH, Le D, et al. (2022) Depth-resolved vascular profile features for artery-vein classification in OCT and OCT angiography of human retina. Biomedical Optics Express. 13: 1121-1130 |
| Le D, Son T, Yao X. (2021) Machine learning in optical coherence tomography angiography. Experimental Biology and Medicine (Maywood, N.J.). 15353702211026581 |
| Yao X, Son T, Kim TH, et al. (2021) Interpretation of anatomic correlates of outer retinal bands in optical coherence tomography. Experimental Biology and Medicine (Maywood, N.J.). 15353702211022674 |
| Alam MN, Le D, Yao X. (2021) Differential artery-vein analysis in quantitative retinal imaging: a review. Quantitative Imaging in Medicine and Surgery. 11: 1102-1119 |