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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 …more
Abstract:
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
 

Keywords

digital pathology convolutional neural networks prostate cancer deep learning
 
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.

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Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatiky
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