A Python-implemented algorithm for three-dimensional reconstruction of the human lumbar spine from DICOM CT data

Abstract

Degenerative disc disease is one of the leading causes of low back pain. Computed tomography (CT) provides high-resolution images of the spine, but a three-dimensional (3D) model is crucial for biomechanical analysis and surgical planning. This paper presents an open-source, fully automated Python algorithm for reconstructing the human lumbar spine from DICOM CT data. This method utilizes Hounsfield unit-based bone segmentation, morphological optimization, and the marching cubes algorithm for surface extraction, ultimately generating an STL mesh.