Thesis supervisor: Miklós Emri
Location of studies (in Hungarian): University of Debrecen Faculty of Informatics Abbreviation of location of studies: DEIK
Description of the research topic:
By combining images provided by hybrid medical imaging systems (PET/CT, PET/MRI, SPECT/CT) and the contents of clinical PACS image databases, new images and parameters can be calculated for enchansing the accuracy of the individual diagnosis. During the research we will develop and characterize automatic and semi-automatic algorithms that can improve the efficiency of daily diagnostic work.
Bibliography
Hanbury A., Müller H., Langs G. (eds) Cloud-Based Benchmarking of Medical Image Analysis. Springer, Cham, https://doi.org/10.1007/978-3-319-49644-3₁3
Wolfgang Birkfellner Applied Medical Image Processing, Second Edition: A Basic Course. Published by CRC Press, 2014
Abraham A, Pedregosa F, Eickenberg M, et al. Machine learning for neuroimaging with scikit-learn. Frontiers in Neuroinformatics. 2014;8:14. doi:10.3389/fninf.2014.00014.
Luigi Landini, Vincenzo Positano, Maria Santarelli (eds) Advanced Image Processing in Magnetic Resonance Imaging (Signal Processing and Communications) 1st Edition, Kindle Edition
Number of students who can be accepted: 1
Deadline for application: 2018-11-15
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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