SWITCH+2026: Stroke and neurovascular diseases Workshop on Imaging and Treatment CHallenges

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Submission Deadline

23:59, July 1, 2026

Date & Location

Date: Sep 27 - Oct 1, 2026

Room: TBD

Keynote speakers

TBD

Overview

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.

Call for papers

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:

  • Novel image processing approaches for detection, classification, segmentation, and quantification of brain vessels, lesions, and abnormalities (e.g., stroke, aneurysms, arteriovenous malformations)
  • Imaging-based and multimodal methods for treatment decision-making, risk stratification, and outcome prediction
  • Image-guided and AI-assisted interventions for navigation and real-time procedural support
  • Imaging-based evaluation of treatment effects and outcomes
  • Image-based approaches for interventional workflow optimization, e.g., LLMs and agentic frameworks
  • Robustness, interpretability, and clinical validation of AI methods

We encourage work involving, among others, the following imaging modalities:

  • CT-variants (CT, CTA, CTP, multi-phase CTA)
  • MR (DWI)
  • X-ray

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.


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Important Dates

  • Apr 8, 2026 Website up
  • Apr 24, 2026 Open for submissions
  • July 1, 2026 Submission deadline
  • July 31, 2026 Decision notification
  • Sep 27 - Oct 1, 2026 MICCAI conference in Strasbourg, France.

Recent Updates

Program

This year's workshop will take place in collaboration with the ISLES, TopBrain and TopAneu challenges as a joint full-day event.

Details: About SWITCH+

Neurovascular Diseases: A Broad Spectrum

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.

Imaging

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.

Goals

  • Introduce key clinical challenges and opportunities in neurovascular imaging — from assessment and diagnosis to treatment decision-making, image-guidance, therapy evaluation, outcome prediction, and longitudinal follow-up.
  • Serve as a central MICCAI forum for clinicians and researchers working on medical image analysis and computational methods across the neurovascular continuum.
  • Present current work and recent methodological advances through peer-reviewed workshop contributions.
  • Foster interdisciplinary exchange and discussion throughout the workshop to connect clinical needs with robust, clinically relevant computational solutions.

The program combines keynote talks by clinical experts in neurovascular imaging and intervention with presentations of ongoing research contributions.

Photos

2025

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2024

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2023

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2018

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2017

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SWITCH+2026 Organizing Committee

Ruisheng Su

TU Eindhoven & Erasmus MC

Linda Vorberg

Pattern Recognition Lab, Friedrich-Alexander-Universität

Adam Hilbert

Head of Machine Learning, Charité Lab for AI in Medicine - CLAIM, Charité - Universitätsmedizin Berlin

Ewout Heylen

Medical Imaging Research Center, KU Leuven

Maria A. Zuluaga

AI4Health Lab, EURECOM, France, School of Biomedical Engineering and Imaging Sciences, King’s College London

Ezequiel de la Rosa

University of Zurich

Leonhard Rist

Pattern Recognition Lab, Friedrich-Alexander-Universität

Markus D. Schirmer

Massachusetts General Hospital, Harvard Medical School

Jiong Zhang

Ningbo-Cixi Institute of Biomedical Engineering, Chinese Academy of Sciences

Theo van Walsum

Biomedical Imaging Group Rotterdam, Erasmus MC

Contact

Please contact us for further questions and comments via email at miccai.switch@gmail.com

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