<scp>SegRef3D</scp> : A Versatile Open‐Source Platform for Artificial Intelligence‐Assisted Segmentation and Three‐Dimensional Reconstruction in Morphological Research

ABSTRACT Accurate and efficient image segmentation is crucial in anatomy, histology, and pathology research. Conventional manual approaches are time‐consuming, whereas fully automated artificial intelligence segmentation requires substantial manual correction owing to inaccuracy. To address this, we developed SegRef3D, a tool integrating the Segment Anything Model 2 with multiframe tracking and interactive refinement functions, enabling streamlined segmentation workflows for anatomical research. SegRef3D is implemented as a standalone, offline desktop application that operates entirely in a local environment, eliminating the need for cloud‐based services. SegRef3D provides a unified workflow from data import to segmentation, object tracking, refinement, and three‐dimensional model export. Users can specify segmentation prompts through bounding box input, track objects across multiple frames with start–end range selection, and refine results using intuitive Add to Mask and Erase from Mask tools. Up to 20 objects can be handled simultaneously, with each assigned a unique color. The software supports the Standard Tessellation Language output for three‐dimensional modeling and includes volume measurement functions. The SegRef3D prototype, called Seg&amp;Ref, has been applied in studies using serial histological sections, correlative microscopy with block‐face imaging, and pelvic magnetic resonance imaging. Building on these applications, SegRef3D further enhances usability and enables a seamless workflow. SegRef3D offers an accessible, efficient, and accurate segmentation environment tailored for morphological and anatomical studies. Combining artificial intelligence‐powered automatic segmentation with human‐guided refinement in a user‐friendly graphical user interface bridges the gap between research needs and computational methods. By supporting applications that span traditional anatomy and modern pathology, SegRef3D provides a versatile platform for integrative morphological analysis. Its open‐source availability ensures its broad applicability in research, education, and clinical training in the anatomical sciences.