Transforming Subarachnoid Hemorrhage Care with Explainable AI

Building, validating, and deploying AI for non-contrast head CT—detecting SAH and quantifying blood volume (SAHV) to speed triage, standardize research, and scale care globally.

View Publications Join Consortium
SAHV AI - Futuristic brain imaging with global collaboration network
~8.09M
SAH Patients Worldwide
1
FDA-Approved Drug
Multi-Site
US & Brazil Consortium

About SAHVAI Lab

A multidisciplinary team advancing AI-driven SAH research

We are a multidisciplinary team of physicians (neurologists, neurosurgery, neuroradiologists), AI-ML imaging scientists that span multiple sites and continents investigating the dose-response relationship of SAHV (SAH hemorrhage Volume) on outcomes.

SAHVAI builds, validates, and deploys AI for non-contrast head CT—detecting SAH and quantifying blood volume (SAHV) to speed triage, standardize research, and scale care globally.

Our Mission

  • Translate to the bedside — Validate SAHV on outcomes from multi-site data sharing with rigorous privacy and governance
  • Accelerate SAH Care ("CODE SAH") — Earlier, more consistent triage and risk stratification
  • Global Scale — Tools that work in both high-tech centers and low-resource settings
  • Open Science — Auditable methods aligned with clinical reality and data privacy

What We Do

Advancing SAH measurement and volumetrics

🧠

Measure SAH on NCCT

We create, train, and evaluate SAHV models to identify SAH patterns quickly and reliably—even in real-world, heterogeneous scans.

  • ABC/2 derived models
  • Computerized segmentation
  • AI automated segmentation
  • 2D, 3D, and 4D reconstruction
📊

Quantify SAH Volume

From ABC/2 to automated 3D segmentation, we deliver reproducible volumes to enable dose–response research and outcome prediction.

  • Compare SAHV models
  • Validate on mortality outcomes
  • Correlate with biomarkers
  • Enable multi-site trials
🔬

Recent Highlights

  • SAHVAI-3D: progress toward automated volumetrics and FAST integration
  • Consortium growth: U.S. and Brazil sites contributing de-identified cases
  • Methods update: benchmarking segmentation loss functions and metrics

Leadership Team

Led by world-class researchers at Mayo Clinic

W. David Freeman, MD

Principal Investigator

Neurocritical Care, Mayo Clinic

Brad Erickson, MD, PhD

Co-Investigator

Neuroradiology and AI, Mayo Clinic

Vishal Patel, MD

Co-Investigator

Neuroradiology, Mayo Clinic

Hamid Tizhoosh, PhD

Co-Investigator

AI Scientist

Alejandro Rabinstein, MD

Co-Investigator

Neurology, Neurocritical Care, Mayo Clinic

Saif Salman, MD

Co-Investigator, Project Manager

Neurosurgery, Mayo Clinic

Plus numerous post-doctoral students, residents, fellows, and medical students

Featured Publications

Peer-reviewed research advancing SAH care

Featured

The ABCs of Subarachnoid Hemorrhage Blood Volume Measurement

Föttinger F, Sharma R, Salman SD, Weston AD, Erickson BJ, Huynh T, Tawk RG, Freeman WD

Journal of the American Heart Association. 2024 Oct 15;13(20):e032195

A simplified quantitative method that predicts outcomes and delayed cerebral ischemia. We derived a simplified mathematical equation over 5 SAH neuroanatomic regions and summated them into SAHV. This simplified SAHV method was comparable to a more labor and time intensive SAHV by computerized manual segmentation.

Full Text PubMed

HEADS-UP: Hemorrhage Evaluation and Detector System for Underserved Populations

Freeman WD, et al.

Mayo Clinic Proceedings: Digital Health. 2023

Initial collaboration with Google on AI-driven intracranial hemorrhage detection for underserved populations, laying the groundwork for SAHVAI Lab's volumetric analysis approach.

Full Text

SAHV-BRaZA Consortium

Bridging continents for better SAH research

SAHVBRazA is bridging continents between US sites and Brazil using a Consortium agreement of limited data set and deidentified data.

SAHVERA International

SAHV European and international Research Alliance — extending global collaboration in subarachnoid hemorrhage volumetrics research.

Benefits of Joining

  • Access to multi-site, de-identified SAH imaging datasets
  • Validated SAHV tools for research and clinical trials
  • Collaboration with leading international researchers
  • Rigorous data privacy and governance frameworks
  • Contribution to open, auditable AI methods
Join the Consortium

Contact Us

Reach out to learn more about SAHVAI Lab

SAHVAI Lab

Mayo Clinic

Jacksonville, Florida

Principal Investigator: W. David Freeman, MD

Email: freeman.william1@mayo.edu

Publications: PubMed Search

SAHVAI Lab is supported by generous philanthropy from
The Louis V. Gerstner Philanthropies