Computational Neurosurgery

Antonio Di Ieva, M.D., Ph.D., FRACS, IFAANS

Antonio Di Ieva is a Professor of Neurosurgery and Associate Professor of Neuroanatomy at Macquarie University (Sydney, Australia), with expertise in neuro-oncology, neurotraumatology, neuroimaging, specialising in microneurosurgery, spine surgery, and pain treatment. He operates at the Macquarie University Hospital and Nepean Hospital in Sydney. Prof Di Ieva has a main interest in neuro-oncology and skull base surgery, with 200 peer-reviewed publications and four textbooks (including the Handbook of Skull Base Surgery, Thieme, and The Fractal Geometry of the Brain, Springer, the latter with the second edition published in 2024), awarded international neurosurgical research awards, including the 2019 John Mitchell Crouch Fellowship, the most prestigious research award of the Royal Australasian College of Surgeons, as well an Australian Research Council (ARC) Future Fellowship. Over the last 5 years, Professor DI Ieva has been granted 8 million Australian dollars for research. He leads international and national seminars and workshops teaching neuroanatomy and neurosurgical approaches, including the first workshop on the white matter dissection technique and connectomics in Australia. He is the world leader in the field of computational neurosurgery, with expertise in the application of computational modeling and Artificial Intelligence to the study of diseases of neurological and neurosurgical relevance. He is the head of the Computational NeuroSurgery (CNS) Lab at Macquarie University, founded by him in 2018, and he is involved in trialing and patenting new surgical devices for medical use. In 2021, he established the first Computational Neurosurgery Fellowship in the world.

Eric Suero Molina, Priv.-Doz. Dr. med., MBA, FEBNS

Dr. Suero is a Neurosurgeon and University Lecturer at the University of Münster, Germany (Chairman: Prof. Dr. med. W. Stummer). He is the director of the minimally invasive Skull Base surgery program of the same hospital.  He has further expertise in Neuro-oncology and Spine surgery. He is the director of the Skull Base & Pituitary Pathologies Hands-on Course in Münster. He acts as a research group leader in optical and hyperspectral imaging of brain tumors at the University of Münster, where he is currently using machine learning and deep learning algorithms to investigate brain tumors. He published over 60 peer-reviewed publications and three book chapters. He furthermore acted as a co-editor of one textbook (Skull Base Surgery, IntechOpen). He graduated in Medicine from the faculty of Medicine of Münster. He underwent neurosurgical training at the same university. He holds a master's degree in business administration in international healthcare management from the Frankfurt School of Business and Management. Dr. Suero was the first computational neurosurgery fellow in the world, pursuing his fellowship at the CNS Lab at Macquarie University.

Sidong Liu, PhD

Sidong Liu is a Senior Research Fellow at Australia Institute of Health Innovation (AIHI), Macquarie University. Dr Liu was awarded an Australian National Health and Medical Research Council (NHMRC) Peter Doherty Biomedical Early Career Fellowship in 2019. This allowed him to establish a new research stream - Translational AI for Healthcare, bringing together a multidisciplinary team at AIHI. Dr Liu has more than 10 years of research experience in the fields of health informatics, medical image computing, and translational healthcare AI. In partnership with Computational NeuroSurgery (CNS) Lab at Macquarie University and the Surgical Planning Lab (SPL) at Harvard Medical School, Dr Liu pioneered the use of deep learning in brain tumour diagnosis based on digital histopathology slides and MRI. Dr Liu has authored >100 peer-reviewed research paper

Computational Neurosurgery: Foundation.- Part I: Foundations of Computational Neurosurgery.- Declaration of Computational Neurosurgery.- Artificial Intelligence Methods.- Deep Learning: A Primer for Neurosurgeons.- Mathematical background of Machine Learning & Deep Learning.- Computational fractal-based Neurosurgery.- Graph theory and modeling of network topology in clinical neurosurgery.- Computer Vision in digital neuropathology.- Bayesian Neural Networks in predictive neurosurgery.- Big data in neurosurgery.- Large Language Models in Neurosurgery.- Part II: Computational Neurosurgery Applications & Translational Aspects.- AI and deep learning in brain tumors.- Meta-transfer Learning for Brain Tumor Segmentation: Within and Beyond Glioma.- Machine learning and radiomics in gliomas.- Machine Learning in fluorescence-guided brain tumor surgery.- AI and computational modeling in skull base surgery.- Applications and Integration of Radiomics for Skull Base Oncology.- Computational modeling and AI in radiation neuro-oncology and radiosurgery.- Multimodal neuroimaging computing: Basics and applications in neurosurgery.- The Brain Connectome for Clinical Neuroscience.- Augmented reality in neurosurgery.- Virtual and Augmented Reality in neurosurgery.- Machine Intelligence in cerebrovascular and endovascular neurosurgery.- Computational fluid dynamics in vascular neurosurgery.- Computational fluid dynamics of cerebrospinal fluid.- Computational Neurosurgery in Deep Brain Stimulation.- Computational modeling, augmented reality, and Artificial Intelligence in spine surgery.- Artificial Intelligence in spine and paravertebral muscles analysis.- Computational prognostic modeling in traumatic brain injury.- Comprehensive overview of computational modeling and artificial intelligence in pediatric neurosurgery.- Machine Learning in Pain Neuromodulation.- Neurosurgery and the brain computer interface.- Ethical aspects of computational neurosurgery.- Explainable AI and Laws in Computational neurosurgery.