| 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 |
| 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), 031401, 2021 | 21 | 2021 |
| SPUD: simultaneous phase unwrapping and denoising algorithm for phase imaging J Pineda, J Bacca, J Meza, LA Romero, H Arguello, AG Marrugo Applied Optics 59 (13), D81-D88, 2020 | 18 | 2020 |
| Active droploids J Grauer, F Schmidt, J Pineda, B Midtvedt, H Löwen, G Volpe, B Liebchen Nature Communications 12 (1), 1-8, 2021 | 15 | 2021 |
| Camera-projector calibration methods with compensation of geometric distortions in fringe projection profilometry: a comparative study R Vargas, AG Marrugo, J Pineda, J Meneses, LA Romero Sociedad Espanola de Optica, 2018 | 14 | 2018 |
| Automated corneal endothelium image segmentation in the presence of cornea guttata via convolutional neural networks JS Sierra, J Pineda, E Viteri, D Rueda, B Tibaduiza, RD Berrospi, A Tello, ... Applications of Machine Learning 2020 11511, 115110H, 2020 | 9 | 2020 |
| Generating density maps for convolutional neural network-based cell counting in specular microscopy images JS Sierra, J Pineda, E Viteri, A Tello, MS Millán, V Galvis, LA Romero, ... Journal of Physics: Conference Series 1547 (1), 012019, 2020 | 9 | 2020 |
| Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting J Pineda, R Vargas, LA Romero, J Marrugo, J Meneses, AG Marrugo PloS one 14 (10), e0223623, 2019 | 9 | 2019 |
| Fourier transform profilometry in labview AG Marrugo, J Pineda, LA Romero, R Vargas, J Meneses Digital Systems, 2018 | 8 | 2018 |
| 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 |
| Fringe quality map for fringe projection profilometry in LabVIEW J Pineda, R Vargas, LA Romero, J Meneses, AG Marrugo Sociedad Espanola de Optica, 2018 | 6 | 2018 |
| 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), 1-13, 2022 | 5 | 2022 |
| Background intensity removal in structured light three-dimensional reconstruction R Vargas, J Pineda, AG Marrugo, LA Romero 2016 XXI Symposium on Signal Processing, Images and Artificial Vision …, 2016 | 4 | 2016 |
| Toward the generation of reproducible synthetic surface data in optical metrology J Pineda, H Altamar-Mercado, LA Romero, AG Marrugo Dimensional Optical Metrology and Inspection for Practical Applications IX …, 2020 | 3 | 2020 |
| Toward an automatic 3D measurement of skin wheals from skin prick tests AG Marrugo, LA Romero, J Pineda, R Vargas, H Altamar-Mercado, ... Dimensional Optical Metrology and Inspection for Practical Applications VIII …, 2019 | 3 | 2019 |
| Roadmap on Deep Learning for Microscopy G Volpe, C Wählby, L Tian, M Hecht, A Yakimovich, K Monakhova, ... ArXiv, 2023 | 2 | 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 | 2 | 2022 |
Giovanni VolpePhysics Department, University of Gothenburg, SwedenVerified email at physics.gu.se
