About Me
Hi, my name’s Daniel and I work as half-time HPC System Administrator at Donostia International Physics Center (DIPC), being part of the management and configuration of the biggest cluster of the Basque Country. The other half of my workday I’m a PhD Candidate at the University of the Basque Country, together with the DIPC, advised by Prof. Ignacio Arganda-Carreras and Prof. Arrate Muñoz-Barrutia.
My general research area is in Biomedical image processing and Computer Vision, focused in the design and development of novel Deep Learning solutions for the segmentation of organelles in large Electron microscope images and across microscope types and modalities.
Publications
2022
CMPB
2022
bioRxiv
A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia
Pedro Gómez-Gálvez, Pablo Vicente-Munuera, Samira Anbari, Antonio Tagua, Carmen Gordillo-Vázquez, Jesús A. Andrés-San Román, Daniel Franco-Barranco, Ana M. Palacios, Antonio Velasco, Carlos Capitán-Agudo, Clara Grima, Valentina Annese, Ignacio Arganda-Carreras, Rafael Robles, Alberto Márquez, Javier Buceta, Luis M. Escudero
2021
Book chapter
Building a Bioimage Analysis Workflow using Deep Learning
Estibaliz Gómez-de-Mariscal, Daniel Franco-Barranco, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2021
Neuroinformatics
Stable deep neural network architectures for mitochondria segmentation on electron microscopy volumes
Daniel Franco-Barranco, Arrate Muñoz-Barrutia, Ignacio Arganda-Carreras
2020
MICCAI
MitoEM Dataset: Large-scale 3D Mitochondria Instance Segmentation from EM Images
Donglai Wei, Zudi Lin, Daniel Franco-Barranco, Nils Wendt, Xingyu Liu, Wenjie Yin, Xin Huang, Aarush Gupta, Won-Dong Jang, Xueying Wang, Ignacio Arganda-Carreras, Jeff W. Lichtman, Hanspeter Pfister
Projects
This project contains a guide to make Semantic Segmentation in Electron Microscopy images using Deep Learning networks such as U-Net (2D/3D), Residual U-Net (2D/3D), Attention based U-Net, FCN or Tiramisu. See docs for more info.
DCRAB monitors submitted jobs into a scheduler system and creates a real time report based on its execution. The report displays some statistics and charts, such as CPU usage, memory consumed by all the processes, Infiniband statistics etc, which may help to understand the behavior of the job at anytime.
Education
Master's degree in Computational Engineering and Intelligent Systems
University of the Basque Country
2018 - 2019 (1 year)
Bachelor's degree in Computer Engineering
University of the Basque Country
2011 - 2015 (4 years)