| Quantitative digital microscopy with deep learning B Midtvedt, S Helgadottir, A Argun, J Pineda, D Midtvedt, G Volpe Applied Physics Reviews 8 (1), 011310, 2021 | 60 | 2021 |
| Fast and accurate nanoparticle characterization using deep-learning-enhanced off-axis holography B Midtvedt, E Olsén, F Eklund, F Höök, CB Adiels, G Volpe, D Midtvedt ACS nano 15 (2), 2240-2250, 2021 | 34 | 2021 |
| Size and refractive index determination of subwavelength particles and air bubbles by holographic nanoparticle tracking analysis D Midtvedt, F Eklund, E Olsén, B Midtvedt, J Swenson, F Höök Analytical chemistry 92 (2), 1908-1915, 2019 | 31 | 2019 |
| Extracting quantitative biological information from bright-field cell images using deep learning S Helgadottir, B Midtvedt, J Pineda, A Sabirsh, C B Adiels, S Romeo, ... Biophysics Reviews 2 (3), 2021 | 21 | 2021 |
| Active droploids J Grauer, F Schmidt, J Pineda, B Midtvedt, H Löwen, G Volpe, B Liebchen Nature Communications 12 (1), 6005, 2021 | 15 | 2021 |
| Simulation of Complex Systems A Argun, A Callegari, G Volpe IOP Publishing, 2021 | 7 | 2021 |
| Quantitative digital microscopy with deep learning B Midtvedt, S Helgadottir, A Argun, J Pineda, D Midtvedt, G Volpe arXiv preprint arXiv:2010.08260, 2020 | 7 | 2020 |
| Geometric deep learning reveals the spatiotemporal fingerprint of microscopic motion J Pineda, B Midtvedt, H Bachimanchi, S Noé, D Midtvedt, G Volpe, ... arXiv preprint arXiv:2202.06355, 2022 | 6 | 2022 |
| Deeptrack-2.0 B Midtvedt, S Helgadottir, A Argun, J Pineda, D Midtvedt, G Volpe | 6 | 2020 |
| Geometric deep learning reveals the spatiotemporal features of microscopic motion J Pineda, B Midtvedt, H Bachimanchi, S Noé, D Midtvedt, G Volpe, ... Nature Machine Intelligence, 1-12, 2023 | 5 | 2023 |
| Single-shot self-supervised object detection in microscopy B Midtvedt, J Pineda, F Skärberg, E Olsén, H Bachimanchi, E Wesén, ... Nature Communications 13 (1), 7492, 2022 | 5 | 2022 |
| Holographic characterisation of subwavelength particles enhanced by deep learning B Midtvedt, E Olsén, F Eklund, F Höök, CB Adiels, G Volpe, D Midtvedt arXiv preprint arXiv:2006.11154, 2020 | 3 | 2020 |
| Roadmap on Deep Learning for Microscopy G Volpe, C Wählby, L Tian, M Hecht, A Yakimovich, K Monakhova, ... ArXiv, 2023 | 2 | 2023 |
| Microplankton life histories revealed by holographic microscopy and deep learning H Bachimanchi, B Midtvedt, D Midtvedt, E Selander, G Volpe Elife 11, e79760, 2022 | 2 | 2022 |
| Single-shot self-supervised particle tracking B Midtvedt, J Pineda, F Skärberg, E Olsén, H Bachimanchi, E Wesén, ... arXiv preprint arXiv:2202.13546, 2022 | 2 | 2022 |
| Dynamic live/apoptotic cell assay using phase-contrast imaging and deep learning Z Korczak, J Pineda, S Helgadottir, B Midtvedt, M Goksör, G Volpe, ... bioRxiv, 2022.07. 18.500422, 2022 | 1 | 2022 |
| Label-free optical quantification of material composition of suspended virus-gold nanoparticle complexes E Olsén, B Midtvedt, A González, F Eklund, K Ranoszek-Soliwoda, ... arXiv preprint arXiv:2304.07636, 2023 | | 2023 |
| Quantitative microplankton tracking by holographic microscopy and deep learning (Conference Presentation) H Bachimanchi, B Midtvedt, D Midtvedt, E Selander, G Volpe Emerging Topics in Artificial Intelligence (ETAI) 2022, PC122040T, 2022 | | 2022 |
| Label-free characterization of biological matter across scales (Conference Presentation) D Midtvedt, E Olsén, B Midtvedt, EK Esbjörner, F Skärberg, B Garcia, ... Emerging Topics in Artificial Intelligence (ETAI) 2022, PC122040P, 2022 | | 2022 |
| Revealing the spatiotemporal fingerprint of microscopic motion using geometric deep learning (Conference Presentation) JDP Castro, B Midtvedt, H Bachimanchi, S Nóe, D Midtvedt, G Volpe, ... Emerging Topics in Artificial Intelligence (ETAI) 2022, PC122040G, 2022 | | 2022 |
