Tracking microtubule ends is more than point tracking
| Autor: | Denis K. Samuylov, Gábor Székely, Gregory Paul |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Image formation
Microtubule dynamics Computer science business.industry Statistical model 02 engineering and technology Photobleaching 030218 nuclear medicine & medical imaging Quantitative Biology::Subcellular Processes 03 medical and health sciences Point tracking 0302 clinical medicine Microtubule 0202 electrical engineering electronic engineering information engineering Fluorescence microscope 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Biological system |
| Zdroj: | ISBI |
| Popis: | Fluorescence microscopy has allowed studying dynamical biological processes in vivo with an ever increasing accuracy. Nonetheless, the physically inherent resolution limits impede the study of very dynamical intracellular processes such as microtubule dynamics. One way to overcome this limited resolution is to reconstruct the underlying object dynamics from the image data by using Bayesian statistics. This framework allows combining statistical models about the image formation process and the dynamical process driving the biological function under scrutiny. In this work we show that the accuracy and robustness of tracking microtubule dynamics can be improved by imposing a weak dynamical prior about the hidden geometry of the microtubule and by accounting for the overall photobleaching. |
| Databáze: | OpenAIRE |
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