Technical Note: SegMed, a 3D Slicer module for standardized post mortem CT segmentation of lower-limb long-bone diaphyses

Abstract Post mortem computed tomography is increasingly used in forensic medicine and anthropology, but quantitative analysis of skeletal and peri-skeletal structures remains limited by heterogeneous anatomical sampling and manual segmentation procedures. This Technical Note presents SegMed, a Python-based 3D Slicer module developed to standardize segmentation and metric extraction from lower-limb long-bone post mortem CT data. In its current version, SegMed is restricted to the lower limb, and the present manuscript focuses on femoral and tibial diaphyseal workflows. The module integrates four steps: semi-automatic extraction of the diaphyseal region from an expert-defined cortical seed point, anatomical alignment of the selected bone segment, Hounsfield unit (HU)-based segmentation of medullary compartments, and optional quantification of peridiaphyseal soft tissues. The module exports quality-control masks, compartment volumes, volumetric fractions, longitudinal profiles, metadata files and analysis-ready CSV/XLSX tables. Optional exploratory indices describing the spatial distribution of segmented compartments are exported for research purposes but are not evaluated in this Technical Note. By combining expert-guided initialization with standardized image processing and structured outputs, SegMed is intended to improve reproducibility in forensic imaging research. The software does not provide diagnostic conclusions, and all outputs require expert visual review and contextual interpretation.