Analýza medicínských obrazů
| Thesis title in Czech: | Analýza medicínských obrazů |
|---|---|
| Thesis title in English: | Medical image analysis |
| Key words: | segmantace|zpracování obrazu|hluboké učení|interpretovatelnost |
| English key words: | segmentation|image processing|deep learning|interpretability |
| Academic year of topic announcement: | 2021/2022 |
| Thesis type: | dissertation |
| Thesis language: | |
| Department: | Department of Software and Computer Science Education (32-KSVI) |
| Supervisor: | doc. RNDr. Elena Šikudová, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 01.09.2021 |
| Date of assignment: | 01.09.2021 |
| Confirmed by Study dept. on: | 14.09.2021 |
| Guidelines |
| Classical medical image analysis topics, i.e. segmentation, registration, computer-aided diagnosis, can be solved with the help of machine learning methods, which have recently been successfully applied to a wide range of domains and have often achieved impressive performances. However, in the case of the medical domain, the predictions potentially affect human lives, thus the results require a high level of accountability and transparency.
The main focus of the work is the selection of suitable algorithms for medical image processing and the development of new ones, which will be appropriate for clinical use. |
| References |
| Gonzalez, R. C. & Woods, R. E. (2008), Digital image processing, Prentice Hall, Upper Saddle River, N.J.
Goodfellow et. al. (2016), Deep Learning, MIT Press Samek et. al. (2019), Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, Lecture Notes in Computer Science, Springer, Cham |