About the Book
This comprehensive and authoritative reference presents the state-of-the-art computational methods applied to the field of neurosurgery. The book brings together leading neuroscientists, neurosurgeons, mathematicians, computer scientists, engineers, ethicists and lawyers, to open the new frontier of computational neurosurgery to a broad audience interested in the translational field of the application of computational models, such as deep learning, to the study of the brain and the practical applications of neurosurgery. The focus is primarily clinical, and there is a solid foundation of research aspects. With forewords by Michael L.J. Apuzzo and Enrico Coiera, the book is organized into 2 sections: (1) tenets of computational modeling, artificial intelligence, computational analysis, and analysis software; (2) computational neurosurgery applications, including neurodiagnostics, neuro-oncology, vascular neurosurgery, all the neurosurgical disciplines, surgical approaches, intraoperative applications, and ethics and legal aspects.
Table of Contents:
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.
About the Author :
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 papers in high impact journals and conferences in his research fields. In 2021, Dr Liu was named the Early Career Researcher of the Year - STEMM Category by Macquarie University.
Carlo Russo, M.Sc. CS
Carlo Russo is a Senior Researcher and Data Scientist at Joint Research Centre (JRC) in Ispra, Italy, and Honorary Research Associate at the Computational NeuroSurgery (CNS) Lab at Macquarie University, Sydney. He works on application and development of algorithms for image analysis in the neurosciences using non-linear geometry, including fractal analysis, and deep learning. He has previously worked more than 15 years at Humanitas Research Hospital in Milan (Italy), where he developed innovative software and hardware aimed to introduce computer aided automatic diagnosis tools both in research and in clinical workflows. He is author and co-author of 30 peer-reviewed publications and 5 patents.
