Bone regeneration is a critical area of research impacting treatment of diseases such as osteoporosis, age-related decline, and orthopaedic implants. A crucial question in bone regeneration is that of bone architectural quality, or how “good” is the regenerated bone tissue structurally? Current methods address typical long bone architecture, however there exists a need for improved ability to quantify structurally relevant parameters of bone in non-standard bone shapes. Here we present a new analysis approach based on open-source semi-automatic methods combining image processing, solid modeling, and numerical calculations to analyze bone tissue at a more granular level using μCT image data from a mouse digit model of bone regeneration. Examining interior architecture, growth patterning, spatial mineral content, and mineral density distribution, these methods are then applied to two types of 6-month old mouse digits – 1) those prior to amputation injury (unamputated) and 2) those 42 days after amputation when bone has regenerated. Results show regenerated digits exhibit increased inner void fraction, decreased patterning, different patterns of spatial mineral distribution, and increased mineral density values when compared to unamputated bone. Our approach demonstrates the utility of this new analysis technique in assessment of non-standard bone models, such as the regenerated bone of the digit, and aims to bring a deeper level of analysis with an open-source, integrative platform to the greater bone community.