ARTIFICIAL INTELLIGENCE

Principal Investigators

Petia Radeva

Full Professor

Machine learning, Computer Vision, Medical Imaging

Research team

 

Simone Balocco

Associate Professor

 

Oliver Diaz

Associate Professor

 

Karim Lekadir

Associate Professor

 

Bhalaji Nagarajan

Early Stage Researcher

 

Ricardo Jorge Rodrigues

Lecturer

Research Interest

 

Artificial intelligence is a mechanical simulation system for collecting, processing, and disseminating knowledge,  with applications in complex data analysis and decision-making.

Technologies & Methods

 

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Active Projects

 

    • An intelligent tool based on Deep learning for Food Intake monitoring of Elderly (LogmeaI4Shape). European Union. Petia Radeva.

 

    • Atorgament d’un ajut de la convocatòria del Programa d’Intensificació de l’Activitat Investigadora Internacional (2020-21). Universitat de Barcelona. Petia Radeva.

 

    • Computer Vision and Machine Learning at the University of Barcelona (CVMLUB). Agència de Gestió d’Ajuts Universitaris i de Recerca. 2017SGR1742. Petia Radeva.

 

    • Contracte del Programa Juan de la Cierva-Formació 2019. Ministerio de Economia y Competitividad. FJC2019-040039-I. Petia Radeva.

 

    • Contracte del Programa Ramon y Cajal. Ministerio de Economia y Competitividad. RYC-2015-17183. Petia Radeva.

 

    • Doctorats industrials 2018. Empresa: Abante & Pongiluppi SL. Agència de Gestió d’Ajuts Universitaris i de Recerca. 2018DI039. Petia Radeva.

 

    • Greenhabit365. European Union. 21105. Petia Radeva.

 

    • LogMeal’s SmartTray: Self-checkout system for selfservice restaurants (Innovadors). Agència de Gestió d’Ajuts Universitaris i de Recerca. Exp. 2019 INNOV 00069. Petia Radeva.

 

    • LOOMING FACTORY. Departament d’Empresa i Coneixement. Generalitat de Catalunya. Ref. 001-P-001643. Petia Radeva.

 

    • Más allá de la Precisión de los Modelos: Icerteza, Explicabilidad y Aprendizaje Entre-modal. Ministerio de Ciencia, Innovación y Universidades. RTI2018-095232-B-C21. Petia Radeva.

 

    • 9 Confidential agreements.

Selected Publications

 

    • Das, M., Gupta, D., Radeva, P., & Bakde, A. M. (2021). Optimized CT-MR neurological image fusion framework using biologically inspired spiking neural model in hybrid ℓ1 − ℓ0 layer decomposition domain. Biomedical Signal Processing and Control, 68, 102535. https://doi.org/10.1016/j.bspc.2021.102535

 

    • Das, M., Gupta, D., Radeva, P., & Bakde, A. M. (2021). Multi-scale decomposition-based CT-MR neurological image fusion using optimized bio-inspired spiking neural model with meta-heuristic optimization. International Journal of Imaging Systems and Technology, 31(4), 2170–2188. https://doi.org/10.1002/ima.22575

 

    • Diaz, O., Kushibar, K., Osuala, R., Linardos, A., Garrucho, L., Igual, L., Radeva, P., Prior, F., Gkontra, P., & Lekadir, K. (2021). Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools. Physica Medica: PM: an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB), 83, 25–37. https://doi.org/10.1016/j.ejmp.2021.02.007

 

    • Glavan, A., Matei, A., Radeva, P., & Talavera, E. (2021). Does our social life influence our nutritional behaviour? Understanding nutritional habits from egocentric photo-streams. Expert Systems with Applications, 171, 114506. https://doi.org/10.1016/j.eswa.2020.114506

 

 

    • Ortíz-Maldonado, V., Rives, S., Castellà, M., Alonso-Saladrigues, A., Benítez-Ribas, D., Caballero-Baños, M., Baumann, T., Cid, J., Garcia- Rey, E., Llanos, C., Torrebadell, M., Villamor, N., Giné, E., Díaz-Beyá, M., Guardia, L., Montoro, M., Català, A., Faura, A., González, E. A., Español-Rego, M., … Delgado, J. (2021). CART19-BE-01: A Multicenter Trial of ARI-0001 Cell Therapy in Patients with CD19+ Relapsed/ Refractory Malignancies. Molecular Therapy: the Journal of the American Society of Gene Therapy, 29(2), 636–644. https://doi.org/10.1016/j.ymthe.2020.09.027

 

    • Pezzano, G., Díaz, O., Ripoll, V. R., & Radeva, P. (2021). CoLe-CNN+: Context learning – Convolutional neural network for COVID-19- Ground-Glass-Opacities detection and segmentation. Computers in Biology and Medicine, 136, 104689. https://doi.org/10.1016/j.compbiomed.2021.104689

 

    • Pezzano, G., Ribas Ripoll, V., & Radeva, P. (2021). CoLe-CNN: Context-learning convolutional neural network with adaptive loss function for lung nodule segmentation. Computer Methods and Programs in Biomedicine, 198, 105792. https://doi.org/10.1016/j.cmpb.2020.105792

 

    • Sarker, M. M. K., Rashwan, H. A., Akram, F., Singh, V. K., Banu, S. F., Chowdhury, F. U. H., Choudhury, K. A., Chambon, S., Radeva, P., Puig, D., & Abdel-Nasser, M. (2021). SLSNet: Skin lesion segmentation using a lightweight generative adversarial network. Expert Systems with Applications, 183. https://doi.org/10.1016/j.eswa.2021.115433

Knowledge transfer & Innovation

 

    • AlGecko Technologies. Spin off. Petia Radeva.