SWITCH+ is a MICCAI workshop focused on imaging, analysis, and computational methods for neurovascular diseases. Building on the original SWITCH workshop on stroke diagnosis and treatment, SWITCH+ expands its scope to include a wider spectrum of neurovascular conditions and vascular pathologies assessed through neuroimaging and related imaging modalities. The main goals of the workshop are 1) to introduce the clinical background of challenges and opportunities in neurovascular diagnosis, treatment, prognosis, and management that are relevant for researchers in the MICCAI field, and 2) to stimulate discussion and exchange around recent advances in imaging and computational methods. To this end, there will be keynotes by clinical experts in neurovascular imaging and intervention, as well as presentations by researchers of ongoing work.
SWITCH+ is soliciting full paper manuscripts to be presented at the workshop. Accepted manuscripts will get a poster or oral presentation during the workshop at MICCAI and will be published in Springer Lecture Notes in Computer Science (LNCS) together with the proceedings of the MICCAI workshop. The following themes are encouraged, but not exhaustive:
We encourage work involving, among others, the following imaging modalities:
Full paper manuscripts should follow the LNCS guidelines for formatting, and have a length of at most eight pages. All submitted manuscripts will be reviewed on applicability to the workshop topic, scientific quality and clinical relevance. Note that we value novel methodology as well as thorough evaluation. Accepted manuscripts will get a poster or oral presentation during the workshop at MICCAI.
Supplementary material is allowed, but will not be included in the proceedings. All papers will go through peer review with at least two blinded reviewers per paper.
Cerebrovascular conditions go well beyond stroke. SWITCH+ addresses the full spectrum of disorders affecting the brain's blood supply, including ischemic and hemorrhagic stroke, intracranial aneurysms, arteriovenous malformations (AVMs), vessel stenosis, cerebral small vessel disease, moyamoya disease, and stroke mimics, among others. Together, these conditions are a leading cause of mortality, long-term disability, and healthcare burden worldwide — and they share a common thread: imaging is central to their diagnosis, treatment, and follow-up.
In current practice, clinical decisions often rely on subjective or semi-quantitative imaging criteria — ASPECTS for ischemic stroke, visual collateral scores, angiographic grading scales. The imaging data available is rich: non-contrast CT, single- and multi-phase CTA, CT perfusion, MRI (DWI, MRA), and DSA for procedural guidance. A growing body of deep learning and computational methods has been proposed for diagnosis (de la Rosa et al., ISLES Challenge 2024), treatment assessment (Su et al., IEEE TMI, 2021), outcome prediction (e.g., Hilbert et al., CiBM, 2019, te Nijenhuis et al, SWITCH, 2023), and vessel morphology analysis (Yang et al., TopBrain challenge 2025) — yet few have been prospectively validated or integrated into routine workflows. Challenges around robustness, interpretability, data heterogeneity, and the time-critical nature of neurovascular care remain open. LLM-based and agentic approaches for workflow optimisation are an emerging frontier. SWITCH+ is the place to explore these questions together.
The program combines keynote talks by clinical experts in neurovascular imaging and intervention with presentations of ongoing research contributions.
Please contact us for further questions and comments via email at miccai.switch@gmail.com
Follow us on LinkedIn