Head model collection for mixed reality navigation in neurosurgical intervention for intracranial lesions

Mixed Reality Navigation (MRN) technology is emerging as an increasingly significant and interesting topic in neurosurgery. MRN enables neurosurgeons to "see through" the head with an interactive, hybrid visualization environment that merges virtual and physical-world elements. Offering immersive, intuitive, and reliable guidance for preoperative and intraoperative intervention of intracranial lesions, MRN showcases its potential as an economically efficient and user-friendly alternative to standard neuronavigation systems. However, the clinical research and development of MRN systems present challenges: recruiting a sufficient number of patients within a limited timeframe is difficult, and acquiring commercially available, medically significant head or skull models at a low cost is equally challenging. To accelerate the development of novel MRN systems and surmount these obstacles, this study introduces a customized dataset tailored for MRN system development and testing in the neurosurgical domain. It encompasses CT/MRI scan data from 19 patients with intracranial lesions and the corresponding three-dimensional (3D) models of anatomical structures and validation references derived from these data. Models are provided in Wavefront object (OBJ) and Stereolithography (STL) file formats, facilitating the development and evaluation of neurosurgical MRN applications.