| Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs V Gulshan, L Peng, M Coram, MC Stumpe, D Wu, A Narayanaswamy, ... Jama 316 (22), 2402-2410, 2016 | 5231 | 2016 |
| Using a deep learning algorithm and integrated gradients explanation to assist grading for diabetic retinopathy R Sayres, A Taly, E Rahimy, K Blumer, D Coz, N Hammel, J Krause, ... Ophthalmology 126 (4), 552-564, 2019 | 267 | 2019 |
| A broadly applicable 3-D neuron tracing method based on open-curve snake Y Wang, A Narayanaswamy, CL Tsai, B Roysam Neuroinformatics 9, 193-217, 2011 | 215 | 2011 |
| Assessing microscope image focus quality with deep learning SJ Yang, M Berndl, D Michael Ando, M Barch, A Narayanaswamy, ... BMC bioinformatics 19, 1-9, 2018 | 133 | 2018 |
| Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue CS Bjornsson, G Lin, Y Al-Kofahi, A Narayanaswamy, KL Smith, W Shain, ... Journal of neuroscience methods 170 (1), 165-178, 2008 | 130 | 2008 |
| The FARSIGHT trace editor: an open source tool for 3-D inspection and efficient pattern analysis aided editing of automated neuronal reconstructions J Luisi, A Narayanaswamy, Z Galbreath, B Roysam Neuroinformatics 9, 305-315, 2011 | 71 | 2011 |
| Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning AV Varadarajan, P Bavishi, P Ruamviboonsuk, P Chotcomwongse, ... Nature communications 11 (1), 130, 2020 | 65 | 2020 |
| Novel 4-D open-curve active contour and curve completion approach for automated tree structure extraction Y Wang, A Narayanaswamy, B Roysam CVPR 2011, 1105-1112, 2011 | 60 | 2011 |
| 3-D image pre-processing algorithms for improved automated tracing of neuronal arbors A Narayanaswamy, Y Wang, B Roysam Neuroinformatics 9, 219-231, 2011 | 51 | 2011 |
| Robust adaptive 3-D segmentation of vessel laminae from fluorescence confocal microscope images and parallel GPU implementation A Narayanaswamy, S Dwarakapuram, CS Bjornsson, BM Cutler, W Shain, ... IEEE transactions on medical imaging 29 (3), 583-597, 2009 | 48 | 2009 |
| Self-aligned Schwann cell monolayers demonstrate an inherent ability to direct neurite outgrowth AM Seggio, A Narayanaswamy, B Roysam, DM Thompson Journal of neural engineering 7 (4), 046001, 2010 | 35 | 2010 |
| Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts L Schiff, B Migliori, Y Chen, D Carter, C Bonilla, J Hall, M Fan, E Tam, ... Nature Communications 13 (1), 1590, 2022 | 14 | 2022 |
| Scientific discovery by generating counterfactuals using image translation A Narayanaswamy, S Venugopalan, DR Webster, L Peng, GS Corrado, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 14 | 2020 |
| Applying deep neural network analysis to high-content image-based assays SJ Yang, SL Lipnick, NR Makhortova, S Venugopalan, M Fan, ... SLAS DISCOVERY: Advancing Life Sciences R&D 24 (8), 829-841, 2019 | 14 | 2019 |
| Batch equalization with a generative adversarial network WW Qian, C Xia, S Venugopalan, A Narayanaswamy, M Dimon, ... Bioinformatics 36 (Supplement_2), i875-i883, 2020 | 10 | 2020 |
| The FARSIGHT project: associative 4D/5D image analysis methods for quantifying complex and dynamic biological microenvironments B Roysam, W Shain, E Robey, Y Chen, A Narayanaswamy, CL Tsai, ... Microscopy and Microanalysis 14 (S2), 60-61, 2008 | 10 | 2008 |
| It's easy to fool yourself: Case studies on identifying bias and confounding in bio-medical datasets S Venugopalan, A Narayanaswamy, S Yang, A Geraschenko, S Lipnick, ... arXiv preprint arXiv:1912.07661, 2019 | 6 | 2019 |
| The FARSIGHT project: associative multi-dimensional image analysis methods for optical microscopy B Roysam, G Lin, C Bjornsson, A Narayanaswamy, Y Chen, W Shaina, ... Rittscher, J. et al, 2008 | 6 | 2008 |
| Multi-temporal globally-optimal dense 3-D cell segmentation and tracking from multi-photon time-lapse movies of live tissue microenvironments A Narayanaswamy, A Merouane, A Peixoto, E Ladi, P Herzmark, ... Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data …, 2012 | 5 | 2012 |
| Deep learning and automated Cell Painting reveal Parkinson’s disease-specific signatures in primary patient fibroblasts L Schiff, B Migliori, Y Chen, D Carter, C Bonilla, J Hall bioRxiv, 2020 | 4 | 2020 |
Dale R WebsterResearch Director, GoogleBestätigte E-Mail-Adresse bei google.com
