2010 NAMIC Project week: Real-Time Volume Rendering for Virtual Colonoscopy

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Home < 2010 NAMIC Project week: Real-Time Volume Rendering for Virtual Colonoscopy


VC-Slicer-75%.jpg

Key Investigators

  • MGH: Yin Wu, June-Goo Lee, Hiro Yoshida
  • BWH/Isomics: Steve Pieper, Ron Kikinis

Objective

Pursure volume rendering that is suitable for real-time and interactive virtual colonoscopy display.

The objectives of this project is to:

  • Examine internal volume rendering engines (open source) availabel in Slicer
  • Provide external volume rendering engines (closed source) for virtual colonoscopy
  • Compare the performance of these volume rendering engines.
  • Compare the advantages and disadvantages of these volume rendering engines in real-time high-quality virtual colonoscopy navigation

Approach, Plan

Several virtual colonoscopy datasets will be rendered by use of the below volume rendering engines.

  • VTK GPU Raycasting in Slicer 3.6 (GLSL)
  • Microsoft research (MSR) volume rendering (CUDA, closed source)

The performance of these volume rendering engines will be compared based on various metrics, including the response to multitouch functions.

Progress

The two volume rendering engines are installed on a single computer equipped with a CUDA-based GPU for rendering the virtual colonoscopy datasets and for performance comparison purposes.

Namic Week Progress

  • Microsoft Research GPU Volume Render, vtk GPU render and NCI GPU Render are installed in the same computer to compare image quality and performance
  • Latest ACE's GPU render features are demoed and has some feature comparison
  • Multi-touch interface on Microsoft Research GPU render is tested, showing inital flying through features
  • Center line of Colon created using 3D Slicer, although the process is very slow due to large segmente colon data
  • Center line created from 3D Imaging Lab, MGH
  • Four GPU Render Comparison table:

GPUCompare-50%.jpg

Delivery Mechanism

A table that shows a comparison of the above two rendering engines in terms of

  • rendering performance and
  • advantages and disadvantages in rendering virtual colonoscopy datasets in clinical settings

will be delivered.

References