Applications of Imaging Techniques in Neurosurgery
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".
Deadline for manuscript submissions: closed (30 June 2025) | Viewed by 1270
Special Issue Editors
Interests: neurosurgery; awake surgery; intra-operative monitoring; fluorescence-guided surgery; vascular neurosurgery
Special Issues, Collections and Topics in MDPI journals
Interests: neurosurgery; neuro-oncology; machine learning; neuroimaging; intra-operative monitoring
Special Issue Information
Dear Colleagues,
Improvements have been brought about in the prognosis of patients undergoing neurosurgical procedures via refinements in technical/technological adjuncts and a better understanding of normal and pathological anatomy due to a more sophisticated depiction of the diseased brain and structures. As such, sound knowledge and familiarity with imaging representations of the central nervous system are vital not only for neuroradiologists from a diagnostic point of view but also for neurosurgeons: treatment decisions, surgical planning, risk, and prognosis estimation require surgeons to be independent evaluators of the results provided by imaging techniques. Sophisticated pre-, intra-, and post-operative techniques have become vital tools of a neurosurgeon’s toolbox.
In this Issue, we will welcome contributions investigating all these aspects in different fields of neurosurgery, for instance, pre-operative radiomics and machine learning techniques for pathology depiction and segmentations, refinements of established tools like navigated transcranial magnetic stimulation for cortical mapping, improvements in white matter segmentations and depiction (tractography), virtual and augmented reality for surgical planning, and the recent development of confocal laser microscopy for intraoperative digital biopsies. Additionally, we plan to accept imaging techniques for vascular surgery, like improvements in flow estimation and depictions, 3D representation of vascular malformations (AVMs, aneurysm, DAVFS), and functional quantifications in chronic and acute ischemic disease to guide surgical decision making.
Prof. Dr. Alessandro Della Puppa
Dr. Giovanni Muscas
Guest Editors
Manuscript Submission Information
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Keywords
- neurosurgery
- imaging
- machine learning
- augmented reality
- surgical planning
- segmentation
- decision making
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