Technical University of Riga
Partner description
The Institute of Smart Computer Technologies in RTU combines academic and research activities in interdisciplinary fields, including information technologies in medical applications.
The Department of Computer Control and Computer Networks has experience of technical leadership and management in scientific projects mostly in medical area.
Team members have knowledge in machine learning, computer image analysis, system architecture and electronic device design. Each area is represented by a lead researcher with scientific and practical experience in their respective field. The experience of the involved scientists is confirmed by publications, participation in projects, defended PhD theses, patent and academical activities.
Relevant FEMaLers and their relevant output
Prof. Dmitrijs Bliznuks
Bio:
Prof. Dmitrijs Bliznuks (m), head of Computer Systems and Computer Networks department, Riga Technical University, has experiences in the following areas: Machine learning, deep neural networks, data mining; Image analysis, computer vision; Cloud systems, web-based calculation systems; Electronic and mechanical engineering, microcontrollers, prototyping; Wireless networks.
Relevant publications:
Tamošiūnas, M., Plorina, E.V., Lange, M., Derjabo, A., Kuzmina, I., Bļizņuks, D., Spigulis, J., “Autofluorescence imaging for recurrence detection in skin cancer postoperative scars”, (2020) Journal of Biophotonics, DOI: 10.1002/jbio.201900162.
Bolochko, K., Bliznuks, D., Uteshev, D., Lihacova, I., Lihachev, A., Chizhov, Y., Bondarenko, A., “Towards to deep neural network application with limited training data: Synthesis of melanoma’s diffuse reflectance spectral images”, (2019) Progress in Biomedical Optics and Imaging – Proceedings of SPIE, DOI: 10.1117/12.2527173.
Bliznuks, D., Lihachev, A., Liepins, J., Uteshev, D., Chizhov, Y., Bondarenko, A., Bolochko, K., “Automated microorganisms activity detection on the early growth stage using artificial neural networks”, (2019) Progress in Biomedical Optics and Imaging – Proceedings of SPIE, DOI: 10.1117/12.2527193.
D.Bliznuks, Y. Chizhov, et al. “Embedded neural network system for microorganisms growth analysis”, Proceedings Volume 11457, Saratov Fall Meeting 2019: Optical and Nano-Technologies for Biology and Medicine, https://doi.org/10.1117/12.2564404, 2020.
Dr. Katrina Bolocko
Bio:
Dr. Katrina Bolocko (f), PhD in engineering, obtained in Riga Technical University in 2011. Since 2018 Vice Dean of Science Activity in Riga Technical University; since 2016 Head of Department of “Image Processing and Computer Graphics Department” in Riga Technical University.
She has several experiences researching in ERDF project “Fast and cost-effective machine learning based system for microbial growth analysis”; in Latvian governmental project “Fast and non-contact optical estimation of micro-organisms activity”; and “Skin cancer early diagnostics accuracy improvement by using neural networks”. Author of several relevant publications on national and International journals.
Relevant publications:
Bolochko, K., Bliznuks, D., Uteshev, D., Lihacova, I., Lihachev, A., Chizhov, Y., Bondarenko, A., “Towards to deep neural network application with limited training data: Synthesis of melanoma’s diffuse reflectance spectral images”, (2019) Progress in Biomedical Optics and Imaging – Proceedings of SPIE, DOI: 10.1117/12.2527173.
Bliznuks, D., Lihachev, A., Liepins, J., Uteshev, D., Chizhov, Y., Bondarenko, A., Bolochko, K., “Automated microorganisms activity detection on the early growth stage using artificial neural networks”, (2019) Progress in Biomedical Optics and Imaging – Proceedings of SPIE, DOI: 10.1117/12.2527193.