Image Analysis Methods for the Characterization of Mitochondrial Morphology and Dynamics
|Kustantaja||Tampere University of Technology|
|Tila||Julkaistu - 30 syyskuuta 2016|
|Nimi||Tampere University of Technology. Publication|
In microscopy studies of mitochondria, it is still common for researchers to rely on visual inspection, as opposed to thorough computational image analysis, for drawing conclusions from image data. This not only limits the amount of data that can be analyzed in a reasonable time, but also introduces human error to the study due to subjective judgement. In the case of mitochondria, the present lack of automatic analysis methods is partly explained by the complex dynamics and morphology of this organelle, which can cause mitochondria to appear vastly different in different environments. Due to this variation in appearance, methods for segmenting and tracking small intracellular particles are often not directly applicable to analyzing mitochondrial images, and instead, special methods may need to be crafted for each application. This thesis is an attempt to facilitate studies on mitochondria by presenting new tools and methods speciﬁcally developed for the quantitative analysis of mitochondrial morphology and dynamics from ﬂuorescence microscope images.
This thesis has three main outcomes. First, we developed a software tool, Mytoe, for quantifying morphological features of mitochondria and estimating their motion from time-lapse ﬂuorescence microscopy. Second, we developed a method for detecting the tips of mitochondria, and demonstrated how these tips can be tracked using a general particle tracking framework. Finally, we propose a novel method for quantifying mitochondrial fragmentation from two-photon microscope images of brain tissue where mitochondria have been ﬂuorescently labeled. We expect these contributions to help provide insights about mitochondrial dynamics and structure in both single-cell imaging and animal disease models.