Computed X-ray Tomography is a non-destructive technique that allows three-dimensional imaging of soil samples’ internal structures, determined by their density and atomic composition variations. The objective of this thesis is to develop an image processing workflow for the quantitative analysis of ice cores using high-resolution CT to determine the volume fraction and vertical distribution of ice, mineral, gas, and organic matter in permafrost cores. I analyzed a 164 cm permafrost core taken from a Yedoma permafrost upland on Kurungnakh Island in the Lena River Delta (northeast Siberia). The obtained results were evaluated and compared with the results of detailed but sample-destructive laboratory analysis. The frozen permafrost core was subjected to a computerized X-ray imaging procedure with a resolution of 50 micrometers. As a result, I obtained 37000 images. Image segmentation was made with a multilevel thresholding method. Threshold values were determined based on the histograms of the images using Java-based image processing software (ImageJ). In addition, the vertical profiles were analyzed in 1-2cm intervals. Bulk densities and volumetric ice content (VIC) were received by freeze-drying and standard laboratory analysis. Here I show that the CT method cannot estimate pore ice in the silty permafrost material at the current resolution but can detect excess ice. CT method allows distinguishing well between ice-saturated mineral soil and organic matter. Automatic thresholding methods cannot obtain an accurate result and perform overall worse than the manual thresholding method. Comparison between CT and laboratory results shows that data derived from both methods overall demonstrate similar patterns but with different magnitudes. The image processing technique to quantify VIC provides a non-destructive analog to traditional laboratory analysis that could help increase the vertical resolution for quantifying mineral, ice, gas, and organic components in permafrost cores and enhance the volumetric estimate.