| List |
| Topic: | Automatická extrakce mimomozkových tkání |
|---|---|
| Department: | Katedra kybernetiky |
| Supervisor: | Ing. Milan Němý, Ph.D. |
| Announce as: | Diplomová práce, Bakalářská práce, Semestrální projekt |
| Description: | Accurate segmentation of brain and non-brain tissue is a crucial step of many applications in brain imaging. For example, all volumetric studies start with brain extraction of structural magnetic resonance (MR) images of the head to estimate the subject’s intracranial volume and they use it later for normalization of results. Manual brain/non-brain segmentation typically takes between 15 min and 2 hr per 3D volume and requires sufficient training. It is, therefore, no wonder that automatic methods are very popular. In this project, you will report on various techniques to tackle this problem and implement one of the methods. Then, you will evaluate its accuracy and compare it with existing tools. Contact email: nemymila@fel.cvut.cz |
| Bibliography: | 1. Smith, Stephen M. "Fast robust automated brain extraction." Human brain mapping 17.3 (2002): 143-155.
2. Shattuck, David W., et al. "Magnetic resonance image tissue classification using a partial volume model." NeuroImage 13.5 (2001): 856-876. 3. Hwang, Hyunho, Hafiz Zia Ur Rehman, and Sungon Lee. "3D U-Net for skull stripping in brain MRI." Applied Sciences 9.3 (2019): 569. 4. Kleesiek, Jens, et al. "Deep MRI brain extraction: a 3D convolutional neural network for skull stripping." NeuroImage 129 (2016): 460-469. |