| DeepImageJ: A user-friendly environment to run deep learning models in ImageJ E Gómez-de-Mariscal, C García-López-de-Haro, W Ouyang, L Donati, ... Nature Methods 18 (10), 1192-1195, 2021 | 116* | 2021 |
| Deep-learning-based segmentation of small extracellular vesicles in transmission electron microscopy images E Gómez-de-Mariscal, M Maška, A Kotrbová, V Pospíchalová, P Matula, ... Scientific reports 9 (1), 13211, 2019 | 33 | 2019 |
| Use of the p-values as a size-dependent function to address practical differences when analyzing large datasets E Gómez-de-Mariscal, V Guerrero, A Sneider, H Jayatilaka, JM Phillip, ... Scientific reports 11 (1), 1-13, 2021 | 25 | 2021 |
| Bioimage model zoo: a community-driven resource for accessible deep learning in bioimage analysis W Ouyang, F Beuttenmueller, E Gómez-de-Mariscal, C Pape, T Burke, ... bioRxiv, 2022.06. 07.495102, 2022 | 12 | 2022 |
| Association of visual and quantitative heterogeneity of 18F-FDG PET images with treatment response in locally advanced rectal cancer: A feasibility study P Martín-González, E Gómez-de-Mariscal, ME Martino, PM Gordaliza, ... PloS one 15 (11), e0242597, 2020 | 12 | 2020 |
| DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches C Spahn, E Gómez-de-Mariscal, RF Laine, PM Pereira, L von Chamier, ... Communications Biology 5 (1), 1-18, 2022 | 11 | 2022 |
| Roadmap on Deep Learning for Microscopy G Volpe, C Wählby, L Tian, M Hecht, A Yakimovich, K Monakhova, ... ArXiv, 2023 | 2 | 2023 |
| DEEPIMAGEJ: Auser-FRIENDLY PLUGIN TO RUN DEEP LEARNING MODELS IN IMAGEJ E Gómez-de-Mariscal, M Unser, A Muñoz-Barrutia, D Sage | 2 | 2019 |
| Building a Bioimage Analysis Workflow Using Deep Learning E Gómez-de-Mariscal, D Franco-Barranco, A Muñoz-Barrutia, ... Bioimage Data Analysis Workflows‒Advanced Components and Methods, 59-88, 2022 | 1 | 2022 |
| EDAM-bioimaging: The ontology of bioimage informatics operations, topics, data, and formats (update 2020) M Kalaš, L Plantard, J Lindblad, M Jones, N Sladoje, MA Kirschmann, ... F1000, 2020 | 1 | 2020 |
| The Cell Tracking Challenge: 10 years of objective benchmarking M Maška, V Ulman, P Delgado-Rodriguez, E Gómez-de-Mariscal, ... Nature Methods, 1-11, 2023 | | 2023 |
| Abstract B046: MLL1 regulates cytokine-driven cell migration and metastasis PR Nair, L Danilova, E Gómez-de-Mariscal, D Kim, R Fan, ... Cancer Research 83 (2_Supplement_2), B046-B046, 2023 | | 2023 |
| MLL1 regulates cytokine-driven cell migration and metastasis PR Nair, L Danilova, E Gómez-de-Mariscal, D Kim, R Fan, ... bioRxiv, 2022.10. 18.512715, 2022 | | 2022 |
| Search for temporal cell segmentation robustness in phase-contrast microscopy videos E Gómez-de-Mariscal, H Jayatilaka, Ö Çiçek, T Brox, D Wirtz, ... arXiv preprint arXiv:2112.08817, 2021 | | 2021 |
| DeepImageJ: Deep learning in bioimage analysis for dummies E Gómez-de-Mariscal, C de-la-Torre-Gutiérrez, A Muñoz-Barrutia, D Sage FocalPlane, 2021 | | 2021 |
| Insights to the characterization of cell motility and intercellular communication through a bioimage analysis perspective E Gómez-de-Mariscal | | 2021 |
| PET Texture Analysis: Does it Have Clinical Significance in Locally Advanced Rectal Cancer? PM Gonzalez, EG de Mariscal, ME Martino, PM Gordaliza, JL Carreras, ... XXXV Congreso anual de la Sociedad Española de Ingeniería Biomédica: Libro …, 2017 | | 2017 |
| Infrared thermography processing to characterize emotional stress: a pilot study EG de Mariscal, A Munoz-Barrutia, J de Frutos, AP González-Marcos, ... IET Digital Library, 2017 | | 2017 |
| Reproducible User-Friendly Deep Learning Workflows for Microscopy Image Analysis with deepImageJ E Gómez-de-Mariscal, C García-López-de-Haro, C de-la-Torre-Gutiérrez, ... | | |
| DeepImageJ: Bridging Deep Learning to ImageJ E Gomez-de-Mariscal, C Garcia-Lopez-de-Haro, L Donati, M Unser, ... | | |
Arrate Muñoz BarrutiaProfessor, Univ. Carlos III de Madrid; Instituto de Investigación Sanitaria Gregorio MarañónVerified email at ing.uc3m.es
