Learning to Predict Prostate Cancer Using Slide-level Annotations – Bc. Michal Jakubík
Bc. Michal Jakubík
Bachelor's thesis
Learning to Predict Prostate Cancer Using Slide-level Annotations
Learning to Predict Prostate Cancer Using Slide-level Annotations
Abstract:
Zapojenie algoritmov umelej inteligencie do diagnostiky rakoviny predstavuje významný pokrok v lekárskej diagnostike. Štandardná metóda trénovania neurónovej siete na detekciu rakoviny si vyžaduje nákladné a časovo náročné podrobné anotácie od patológov. V tejto práci je natrénovaných niekoľko modelov konvolučných neurónových sietí na datasetoch, ktoré disponujú iba informáciou o prítomnosti rakovinového …moreAbstract:
The involvement of artificial intelligence algorithms in cancer diagnosis represents a significant advancement in medical diagnostics. A standard method of training a neural network for cancer detection requires expensive and time-consuming detailed annotations from expert pathologists. In this thesis, several convolutional neural network models are trained on datasets which only posses information …more
Language used: English
Date on which the thesis was submitted / produced: 23. 5. 2024
Identifier:
https://is.muni.cz/th/wojxp/
Thesis defence
- Date of defence: 24. 6. 2024
- Supervisor: RNDr. Vít Musil, Ph.D.
- Reader: doc. RNDr. Petr Novotný, Ph.D.
Citation record
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsBachelor programme / field:
Informatics / Informatics
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