Corneal neovascularization assesment using machine learning methods

• Thesis title in Czech: Vyhodnocení neovaskularizace rohovky metodami strojového učení
• Thesis title in English: Corneal neovascularization assesment using machine learning methods
• Key words: hluboké učení|detekce cév|rohovka|neovaskularizace rohovky|machine learning|segmentace obrázku|medical image|U-Net
• English key words: deep learning|vessels detection|cornea|corneal neovascularization|machine learning|image segmentation|medical image|U-Net
• Academic year of topic announcement: 2022/2023
• Thesis type: rigorosum thesis
• Thesis language: angličtina
• Department: Department of Software Engineering (32-KSI)
• Supervisor: doc. RNDr. Elena Šikudová, Ph.D.
• Author: hidden - assigned and confirmed by the Study Dept.
• Date of registration: 02.01.2023
• Date of assignment: 02.01.2023
• Confirmed by Study dept. on: 02.01.2023
• Date of electronic submission: 03.01.2023

Guidelines

Student vypracuje rešerši detekce cév na rohovce. Vybere vhodnou metodu a vylepsi ji. Ve spolupráci s lékaři oftalmologické kliniky FNKV implementuje metodu posuzování neovaskularizce rohovky.

References

Ian Goodfellow and Yoshua Bengio and Aaron Courville, "Deep Learning", MIT Press 2016, http://www.deeplearningbook.org

Deli Krizova, Magdalena Vokrojova, Katerina Liehneova, Pavel Studeny, "Treatment of Corneal Neovascularization Using Anti-VEGF Bevacizumab", Journal of Ophthalmology, vol. 2014, Article ID 178132, 7 pages, 2014. https://doi.org/10.1155/2014/178132