The Joint Research Unit Biomedical Imaging Unit FISABIO-CIPF is specialized in anonymization, curation and processing of medical image data through the application of artificial intelligence and radiomics techniques.
This Unit leads the Medical Image Bank of the Valencian Community, BIMCV (https://bimcv.cipf.es/). It also contributes to the BIDS community (Brain Imaging Data Structure, https://bids.neuroimaging.io/index.html) by developing the BEP025 (MIDS-BIDS: Medical Population Imaging Data Structure).
The Joint Research Unit Biomedical Imaging Unit FISABIO-CIPF is provided with a unique computational infrastructure with some of the best resources in the Valencian Community for biomedical research.
This entity is currently collaborating on the development of image data lakes and predictive models based on artificial intelligence techniques in several projects (DeepHealth: Deep-learning and hpc to boost biomedical applications for health, TARTAGLIA: Federated network to accelerate the application of Artificial Intelligence in the Spanish Health System, IMPaC-DATA: development of a data integration and analysis environment that includes the ability to resolve questions from clinical groups and formulated by the Predictive Medicine and Genomic Medicine Programs).
It is also focused on research in the field of neuroimaging.
Presentation
Get to know us better
Research Staff
The people who make it all possible
María De La Iglesia Vayá
miglesia@cipf.es
Maria Luisa Caparrós Redondo
Julio Domenech Fernández
José Molina Mateo
Elena Oliver García
eoliver@cipf.es
Hector Carceller Cerdá
hcarceller@cipf.es
Adolfo López Cerdán
alopez@cipf.es
Irene Pérez Díez
iperez@cipf.es
Silvia Nadal Almela
snadal@cipf.es
Jose Manuel Saborit Torres
jmsaborit@cipf.es
Joaquim ángel Montell Serrano
jamontell@cipf.es
Publications
Our scientific contributions
PadChest: A large chest x-ray image dataset with multi-label annotated reports.
Bustos A, Pertusa A, Salinas JM and de la Iglesia-Vayá M
MEDICAL IMAGE ANALYSIS, 2020 Dec, DOI: 10.1016/j.media.2020.101797, Vol. 66, pag. 101797-101797
Functional Signatures in Non-Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis of Sex-Based Differences in Transcriptomic Studies
I. PEREZ-DIEZ, M. HIDALGO, P. MALMIERCA-MERLO, Z. ANDREU, S. ROMERA-GINER, R. FARRAS, M. DE LA IGLESIA-VAYA, M. PROVENCIO, A. ROMERO and F. GARCIA-GARCIA
Cancers, 2021 Jan, DOI: 10.3390/cancers13010143, Vol. 13, pag.
COVID-19 detection in X-ray images using convolutional neural networks.
Arias-Garzón D, Alzate-Grisales JA, Orozco-Arias S, Arteaga-Arteaga HB, Bravo-Ortiz MA, Mora-Rubio A, Saborit-Torres JM, Serrano JÁM, de la Iglesia Vayá M, Cardona-Morales O and Tabares-Soto R
Machine Learning With Applications, 2021 Dec, DOI: 10.1016/j.mlwa.2021.100138, Vol. 6, pag. 100138-100138
Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging.
de la Iglesia-Vaya M
NEURON, 2022 Jan, DOI: 10.1016/j.neuron.2021.10.015, Vol. 110, pag. 16-20
The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data.
Bannier E, Barker G, Borghesani V, Broeckx N, Clement P, Emblem KE, Ghosh S, Glerean E, Gorgolewski KJ, Havu M, Halchenko YO, Herholz P, Hespel A, Heunis S, Hu Y, Hu CP, Huijser D, de la Iglesia Vayá M, Jancalek R, Katsaros VK, Kieseler ML, Maumet C, Moreau CA, Mutsaerts HJ, Oostenveld R, Ozturk-Isik E, Pascual Leone Espinosa N, Pellman J, Pernet CR, Pizzini FB, Trbalic AŠ, Toussaint PJ, Visconti di Oleggio Castello M, Wang F, Wang C and Zhu H
HUMAN BRAIN MAPPING, 2021 May, DOI: 10.1002/hbm.25351, Vol. 42, pag. 1945-1951
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