| Téma: | Deep learning for tumor detection from histopathological images
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| Vedoucí: | prof. Dr. Ing. Jan Kybic , Jan Hering Dipl.-Math.
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| Vypsáno jako: | Diplomová práce,Bakalářská práce,Individuální projekt,Dobrovolná odborná práce,Semestrální projektPráce v týmu a její organizace
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| Popis: | The task is to develop a deep learning (convolutional neural network) method to detect cancerous tissue in colorectal histopathological images. Several network architectures should be tried and the performance compared with a classical solution. In some cases, only weak annotations are available - we know whether a subject is healthy or not but a precise location of the lesion is not available. This leads to so-called multiple instance learning methods. Students will be able to compare their results with other authors in the frame of the CAMELYON challenge (https://camelyon17.grand-challenge.org)
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| Pokyny: | Recommended implementation languages are Python or Julia.
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| Realizace: | SW projekty
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| Vypsáno dne: | 13.05.2019
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| Max. počet studentů: | 6
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| Přihlášení studenti: |
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