| Quantitative digital microscopy with deep learning B Midtvedt, S Helgadottir, A Argun, J Pineda, D Midtvedt, G Volpe Applied Physics Reviews 8 (1), 2021 | 123 | 2021 |
| 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 5 (1), 71-82, 2023 | 53 | 2023 |
| 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 | 49 | 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 | 48 | 2019 |
| 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 | 46 | 2022 |
| 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 | 39 | 2021 |
| Active droploids J Grauer, F Schmidt, J Pineda, B Midtvedt, H Löwen, G Volpe, B Liebchen Nature Communications 12 (1), 6005, 2021 | 26 | 2021 |
| Simulation of Complex Systems A Argun, A Callegari, G Volpe IOP Publishing, 2021 | 25 | 2021 |
| Roadmap on deep learning for microscopy G Volpe, C Wählby, L Tian, M Hecht, A Yakimovich, K Monakhova, ... ArXiv, 2023 | 21 | 2023 |
| Quantitative evaluation of methods to analyze motion changes in single-particle experiments G Muñoz-Gil, H Bachimanchi, J Pineda, B Midtvedt, M Lewenstein, ... arXiv preprint arXiv:2311.18100, 2023 | 11 | 2023 |
| Deeptrack 2.0 B Midtvedt, S Helgadottir, A Argun, J Pineda, D Midtvedt, G Volpe | 10 | 2020 |
| Quantitative digital microscopy with deep learning B Midtvedt, S Helgadottir, A Argun, J Pineda, D Midtvedt, G Volpe arXiv preprint arXiv:2010.08260, 2020 | 9 | 2020 |
| Microplankton life histories revealed by holographic microscopy and deep learning H Bachimanchi, B Midtvedt, D Midtvedt, E Selander, G Volpe Elife 11, e79760, 2022 | 7 | 2022 |
| Nanoalignment by critical Casimir torques G Wang, P Nowakowski, N Farahmand Bafi, B Midtvedt, F Schmidt, ... Nature Communications 15 (1), 5086, 2024 | 5 | 2024 |
| 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 | 4 | 2023 |
| Single-shot self-supervised particle tracking B Midtvedt, J Pineda, F Skärberg, E Olsén, H Bachimanchi, E Wesén, ... arXiv preprint arXiv:2202.13546, 2022 | 4 | 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 |
| Cross-modality transformations in biological microscopy enabled by deep learning D Hassan, J Domínguez, B Midtvedt, H Klein Moberg, J Pineda, ... Advanced Photonics 6 (6), 064001-064001, 2024 | 1 | 2024 |
| 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 |
| Self-assembly of defined core–shell ellipsoidal particles at liquid interfaces J Eatson, S Bauernfeind, B Midtvedt, A Ciarlo, J Menath, G Pesce, ... Journal of Colloid and Interface Science 683, 435-446, 2025 | | 2025 |
