Detail of the student project

Topic:Deep learning for tumor detection from histopathological images
Supervisor:Prof. Dr. Ing. Jan Kybic , Jan Hering Dipl.-Math.
Description: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 (

Instruction:Recommended implementation languages are Python or Julia.
Realization form:SW projekty
Max.number of students:6

Warning: the registration to the PTO can be canceled only by supervisor.
Responsible person: Petr Pošík