Filtration is crucial for separating solids and liquids in various industries. Understanding slurry properties and filter cake structures is essential for optimising filtration performance. Conventional methods focus on interpreting filtration data to improve the understanding of filtration mechanisms. However, examining fragile filter cakes is challenging, and current techniques often alter their structure. Conventional methods only provide an average representation of cake porosity, neglecting variations in porosity and pore distribution across the cake thickness. This study introduces the Digital cake analysis, a non-destructive technique for evaluating filter cake structure. Filtration experiments using a custom-built unit were conducted on coal slurries to obtain filter cake samples. X-ray-microcomputed tomography (µCT) imaging was utilized for cake analysis. Image enhancement techniques were employed to improve the quality of the µCT images. The enhanced images were segmented into three phases (resolved pore, subresolution pore, and solid phases) for quantitative analysis. This segmentation technique allocated partial pore volume to voxels in the subresolution phase based on their intermediate grey-scale intensity, enabling more accurate porosity calculations. Unlike conventional methods, this approach computed porosity values for resolved (100% void) and subresolution (partially void) pores. This image segmentation technique facilitated accurate computations of porosity, pore size distribution, and pore properties, significantly advancing the understanding of cake structures. Digital cake analysis produced porosity measurements similar to the experimental results.