Löke, Niek (2024) Live Cell Image Segmentation for STED Microscopy. Master's Thesis / Essay, Computing Science.
|
Text
mCS2024LokeNI.pdf Download (4MB) | Preview |
|
![[img]](https://fse.studenttheses.ub.rug.nl/style/images/fileicons/text.png) |
Text
toestemming.pdf Restricted to Registered users only Download (144kB) |
Abstract
Stimulated Emission Depletion (STED) microscopy is an advanced fluorescence microscopy technique that manages to break the diffraction limit of light, allowing for super-resolution imaging of cellular structures. This is achieved by the use of fluorophores, fluorescent molecules that can be selectively excited and quenched by two high-intensity lasers. However this intense light can detrimentally affect both the fluorophores’ ability to emit light, and the viability of the observed cells. The most reliable way to reduce this damage is to limit the exposure to the STED lasers by reducing the dwell time. This thesis proposes a method to get the most vital information from low dwell time images using segmentation maps. To accomplish this a segmentation tool for Astronomy, MTObjects, is used as a starting point and adapted for the use on live-cell images. These adaptations include improved noise-detection, adaptive blurring, image reconstruction, and a novel approach to inner-segmentation. Consequently, a clear picture is created of how much information is retained for each lower dwell time selection, demonstrating that most vital information is preserved for all but the lowest dwell times.
| Item Type: | Thesis (Master's Thesis / Essay) |
|---|---|
| Supervisor name: | Bunte, K. and Wilkinson, M.H.F. |
| Degree programme: | Computing Science |
| Thesis type: | Master's Thesis / Essay |
| Language: | Dutch |
| Date Deposited: | 04 Sep 2024 13:28 |
| Last Modified: | 04 Sep 2024 13:28 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/34194 |
Actions (login required)
 |
View Item |