Augmented reality guidance in cerebrovascular surgery using microscopic video enhancement

Abstract

Cerebrovascular surgery treats vessel abnormalities in the brain and spinal cord, including arteriovenous malformations (AVMs) and aneurysms. These procedures often involve clipping the vessels feeding blood to these abnormalities, making accurate classification of blood vessel types (feeding versus draining) important during surgery. Previous work to guide the intraoperative identification of the vessels included augmented reality (AR) using pre-operative images, injected dyes, and Doppler ultrasound, but each with their drawbacks. The authors propose and demonstrate a novel technique to help differentiate vessels by enhancing short videos of a few seconds from the surgical microscope using motion magnification and spectral analysis, and constructing AR views that fuse the analysis results as intuitive colourmaps and the surgical microscopic view. They demonstrated the proposed technique retrospectively with two real cerebrovascular surgical cases: one AVM and one aneurysm. The results showed that the proposed technique can help characterise different vessel types (feeding and draining the abnormality), which agree with those identified by the operating surgeon.

Keywords

• biomedical ultrasonics
• spectral analysis
• medical image processing
• neurophysiology
• blood vessels
• blood
• brain
• augmented reality
• surgery
• image enhancement
• video signal processing
• image motion analysis
• AVM
• aneurysm
• augmented reality guidance
• cerebrovascular surgery
• microscopic video enhancement
• vessel abnormalities
• brain
• spinal cord
• arteriovenous malformations
• accurate classification
• blood vessel types
• intraoperative identification
• injected dyes
• Doppler ultrasound
• spectral analysis
• surgical microscopic view
• preoperative images
• motion magnification