Artificial Intelligence
Principal Investigators
Petia Radeva
Full Professor
Karim Lekadir
Assistant Professor
Research Team
Bhalaji Nagarajan
Early Stage Researcher
Simone Balocco
Associate Professor
Oliver Diaz
Associate Professor
Ricardo Marques
Assistant Professor
Active Projects
Trustworthy Artificial Intelligence for Personalised Risk Assessment in Chronic Heart Failure
Unió Europea. Grant agreement ID: 101080430. Karim.
International Clinical Validation of Radiomics Artificial Intelligence for Breast Cancer Treatment Planning
Unió Europea. Grant agreement ID: 101057699. Karim.
MUSAE: a human-centred factory for a future technological sustainable development driven by arts (MUSAE)
Unió Europea. 101070421. Petia.
Hacer que el aprendizaje profundo funcione en el mundo real: una perspectiva centrada en los datos
Ministerio de Ciencia e Innovación (MICINN). PID2022-141566NB-I00. Petia.
Ajut per incentivar i consolidar la recerca d’excel·lència ja existent a les universitats públiques de Catalunya. Programa ICREA Academia 2022.
Fundació Institució Catalana de Recerca i Estudis Avançats (ICREA). Petia.
Una herramienta digital para la estimación de la cantidad de comida usando deep learning
Ministerio de Ciencia e Innovación. PDC2022-133642-I00. Petia.
Modelització del comportament i calibració de sensors de gas basats en Deep learning (DeepSens) (ACE053/22/000029)
ACCIÓ. Agència de Suport a l'Empresa Catalana. ACE053/22/000029. Petia.
Robo STEAM – Inclusive Technologies
Education, Audiovisual and Culture Executive Agency (EACEA). 2022-1-BG01-KA220-VET-000089434. Petia.
Artificial Intelligence and Biomedical Applications (AIBA)
Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR). 2021 SGR 01094. Petia.
Inclusive Artificial Intelligence for Accessible Medical Imaging Across Resource-Limited Settings
Unió Europea. Grant agreement ID: 101044779. Karim.
A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology
Unió Europea. Grant agreement ID: 952103. Karim.
A European Health Data Toolbox for Enhancing Cardiology Data Interoperability, Reusability and Privacy
Unió Europea. Grant agreement ID: 101057849. Karim.
Selected publications
Andreasen, L. A., Feragen, A., Christensen, A. N., Thybo, J. K., Svendsen, M. B. S., Zepf, K., Lekadir, K., & Tolsgaard, M. G. (2023). Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization. Scientific Reports, 13(1), 2221. https://doi.org/10.1038/s41598-023-29105-x
Chatterjee, S., Saad, F., Sarasaen, C., Ghosh, S., Krug, V., Khatun, R., Mishra, R., Desai, N., Radeva, P., Rose, G., Stober, S., Speck, O., & Nürnberger, A. (2024). Exploration of Interpretability Techniques for Deep COVID-19 Classification Using Chest X-ray Images. Journal of Imaging, 10(2), 45. https://doi.org/10.3390/jimaging10020045
Momeny, M., Neshat, A. A., Jahanbakhshi, A., Mahmoudi, M., Ampatzidis, Y., & Radeva, P. (2023). Grading and fraud detection of saffron via learning-to-augment incorporated Inception-v4 CNN. Food Control, 147, 109554. https://doi.org/10.1016/j.foodcont.2022.109554
Naderi, H., Ramírez, J., van Duijvenboden, S., Pujadas, E. R., Aung, N., Wang, L., Anwar Ahmed Chahal, C., Lekadir, K., Petersen, S. E., & Munroe, P. B. (2023). Predicting left ventricular hypertrophy from the 12-lead electrocardiogram in the UK Biobank imaging study using machine learning. European Heart Journal – Digital Health, 4(4), 316–324. https://doi.org/10.1093/ehjdh/ztad037
Osuala, R., Kushibar, K., Garrucho, L., Linardos, A., Szafranowska, Z., Klein, S., Glocker, B., Diaz, O., & Lekadir, K. (2023). Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging. Medical Image Analysis, 84, 102704. https://doi.org/10.1016/j.media.2022.102704
Osuala, R., Skorupko, G., Lazrak, N., Garrucho, L., García, E., Joshi, S., Jouide, S., Rutherford, M., Prior, F., Kushibar, K., Díaz, O., & Lekadir, K. (2023). medigan: a Python library of pretrained generative models for medical image synthesis. Journal of Medical Imaging, 10(06). https://doi.org/10.1117/1.JMI.10.6.061403
Rauseo, E., Salih, A., Raisi-Estabragh, Z., Aung, N., Khanderia, N., Slabaugh, G. G., Marshall, C. R., Neubauer, S., Radeva, P., Galazzo, I. B., Menegaz, G., & Petersen, S. E. (2023). Ischemic Heart Disease and Vascular Risk Factors Are Associated With Accelerated Brain Aging. JACC: Cardiovascular Imaging, 16(7), 905–915. https://doi.org/10.1016/j.jcmg.2023.01.016
Sendra-Balcells, C., Campello, V. M., Torrents-Barrena, J., Ahmed, Y. A., Elattar, M., Ohene-Botwe, B., Nyangulu, P., Stones, W., Ammar, M., Benamer, L. N., Kisembo, H. N., Sereke, S. G., Wanyonyi, S. Z., Temmerman, M., Gratacós, E., Bonet, E., Eixarch, E., Mikolaj, K., Tolsgaard, M. G., & Lekadir, K. (2023). Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries. Scientific Reports, 13(1), 2728. https://doi.org/10.1038/s41598-023-29490-3