Anatomical annotation on vascular structure in volume rendered images

Area of Science:

• Medical Imaging
• Computer Graphics
• Surgical Navigation

Background:

• Precise annotation of vascular structures is crucial for computer-assisted surgery.
• Identifying individual vessel branches aids surgeons in complex procedures.

Purpose of the Study:

• To develop an automated method for annotating vessels on volume rendered images.
• To enhance surgical guidance by rendering vessel names directly onto 3D medical visualizations.

Main Methods:

• A two-pass rendering process is employed.
• The first pass generates vessel surface models and renders names onto them, creating a depth buffer.
• The second pass uses ray casting volume rendering, incorporating the depth buffer to blend annotated vessel names with the volume rendered image.

Main Results:

• Vessel names were successfully rendered onto corresponding vessel surfaces in volume rendered images.
• The method achieved this annotation with a computational cost comparable to standard volume rendering.
• Effectiveness was demonstrated through an automated annotation system for abdominal arteries.

Conclusions:

• The proposed two-pass rendering method provides effective automated annotation of vascular structures in 3D medical images.
• This technique offers significant potential for clinical applications, particularly in image-guided surgery.
• The method integrates seamlessly with existing volume rendering algorithms, offering a practical solution for enhancing surgical visualization.