Study Of 3D Neuronal Morphology Of Barrel Cortex Based On The Golgi-stained Mouse Brain Image Set

The diversity of neuronal morphologies is critical to brain functions, while brain disorders are always accompanied with variations of neuronal morphology. Consequently, for the purpose of deciphering the brain mystery, it's of great significance to study the neuronal morphology, especially the morphology of the cortical neurons. As one of the most important accesses to study neuronal morphology, Golgi-staining is capable of labeling neurons in brain tissue in a sparse and random style. However, the traditional Golgi-staining is usually performed on brain tissue slices with certain axial thickness, thus displaying neuronal morphology in two-dimension(2D). Combining the modified Golgi-Cox staining with the Micro-Optical Sectioning Tomography(referred to as MOST) can be employed to obtain the Golgi-stained whole mouse brain image set with high spatial resolution, providing the new solution to study neuronal morphology in three-dimension(3D).The thesis has selected the neurons in barrel cortex as the research object. Based on the two Golgi-stained-MOST mouse brain image sets, the thesis has studied the whole pipeline covering preprocessing the raw image sets to reconstructing and analyzing the 3D digitalized neuronal morphologies of the neurons in the barrel cortex. Specifically, the thesis has included these three aspects. Firstly, for preprocessing the raw image sets, instead of calculating cutting parameters using intensity distribution, the thesis has adopted the fixed cutting parameters using sampling averaging to eliminate the potential data loss; and before removing the periodical noise, the thesis has uniformed the image sizes and stitched the stripe images to the entire coronal sections in the meantime, ensuring the accuracy and efficiency of the following image segmentation and optimizing the storage strategy; and via referring to the classic mouse brain atlas and the minimum intensity projections, the thesis has successfully located the barrel cortex B1 SF in the 3D image sets. Secondly, based on the MOST image stack of the barrel cortex, the thesis has reconstructed the 3D morphologies of 50 neurons in the barrel cortex using semi-automatic and interactive image segmentation method. Finally, the thesis has analyzed the reconstructed digitalized 3D morphologies with the 6 selected morphological parameters, and has compared the results with the related ones provided by the famous neuronal morphology database Neuro Morpho.org. The study pipeline in this thesis has the potential to be expanded and applied to multiple brain regions in one brain sample, even in the whole mouse brain, providing the new vision into the study of the fine neuronal morphologies in 3D by exploring the MOST whole mouse brain image set with high spatial resolution.