In this work, we study the phases of image processing chain of microtomographic imag- ing in order to obtain reliable results while optimizing the time spent on denoising and segmentation. We consider that the decisions made at the early phases of the processing chain are most important and the selection made there essentially determine the overall quality of imaging process. We also compare here various denoising method qualita- tively, however, we think that the pure noise removal ability is not the only requirement for noise removal in microtomographic images. By proper denoising we can affect selec- tion of segmentation methods and, thus, also the quality of the analysis. Additionally, at the end, we also review the image segmentation and analysis methods commonly used in microtomographic imaging.
|Award date||16 Dec 2015|
|Publication status||Published - 2015|
|MoE publication type||G5 Doctoral dissertation (article)|