Research Programs
CNRF supports collaboration across neurosurgery and computational science. These priorities guide project development; each study defines its scope, participation requirements, and methods.
[01]
Artificial Intelligence in Neurosurgery
Supporting research in artificial intelligence, machine learning, and deep learning for neurosurgical research, planning, prediction, workflow optimization, and clinical decision support.
[02]
Computational Radiosurgery
Advancing data-driven and computational approaches to stereotactic radiosurgery, computational radiosurgery, treatment planning, dose modeling, outcome prediction, and personalized radiosurgical care.
[03]
Neuroimaging, Radiomics, and Connectomics
Supporting research in neuroimaging, tractography, connectomics, brain mapping, radiomics, imaging biomarkers, and quantitative imaging science.
[04]
Surgical Data Science
Developing methods to transform neurosurgical data into actionable insights through analytics, registries, predictive modeling, and computational infrastructure.
[05]
Computational Neuro-Oncology
Advancing computational approaches for brain tumors, metastases, gliomas, meningiomas, skull base tumors, imaging biomarkers, treatment response prediction, and personalized neuro-oncology.
[06]
Functional Neurosurgery and Brain Mapping
Supporting computational approaches to functional neurosurgery, movement disorders, epilepsy, pain, brain mapping, connectomics, and patient-specific targeting.
[07]
Robotics and Image-Guided Neurosurgery
Supporting innovation in robotics, image-guided neurosurgery, surgical navigation, intraoperative technologies, and computational planning.
[08]
Clinical Decision-Support Systems
Supporting the responsible development and validation of computational tools for neurosurgical decision-making.
[09]
Digital Health and Neurosurgical Informatics
Advancing digital health, neurosurgical informatics, clinical data infrastructure, and translational neurotechnology.
[10]
Responsible AI, Ethics, and Governance
Advancing ethical, transparent, validated, monitored, and clinically responsible development of AI and computational tools in neurosurgery.
[11]
Education and Training
Identify learning priorities in computational methods, research design, and responsible AI for neurosurgery.
[12]
Multicenter Registry and Data Infrastructure
Develop shared definitions and governance approaches for study-specific registries and multicenter research data.
[13]
Translational Innovation and Technology Development
Supporting the translation of computational tools, software, algorithms, decision-support systems, and emerging technologies into responsible clinical and research applications.