Two-photon laser scanning microscopy is a modern method of in vivo neurophysiological research, capable of imaging up to hundreds of neurons at once. However, this method produces a large amount of data, difficult to process and analyze manually. This thesis presents Two-Photon Processor, a new toolkit for complex processing of data from two-photon microscope. During the work on this thesis, we designed the SeNeCA segmentation algorithm for detection of neurons in full-frame recording from a two-photon microscope. SeNeCA combines high speed and high quality of segmentation and, according to our evaluation, it currently is the best algorithm for segmentation of neurons in in vivo data. Two- Photon Processor is already routinely used in the Institute of Experimental Medicine of the ASCR, Department of Auditory Neuroscience, and it was published in the Journal of Neurophysiology.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:330734 |
| Date | January 2013 |
| Creators | Tomek, Jakub |
| Contributors | Novák, Ondřej, Krajíček, Václav |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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