Goals

• Understand, and judge the advantages and disadvantages of the medical visualization algorithms, as well as their applicability to a specific medical problem.
• Propose suitable solutions to a problem, backed by sound knowledge of the underlying theory and the practical possibilities.
• Design, implement, test and discuss these solutions, consisting of a number of medical visualization algorithms.

Introduction (L1)

• Medical Imaging
• General Intro Vis
  • 3 goals of Vis (Communicate, analyze, explore)
  • Vis Pipeline

Basic Concepts (L1-2)

• Definition Image => digital images; Sampling and Quantization Intro (L1)
• Beyond Scalar Images: Vector fields (Tensors, High Dim?) (L1)
• Basics of Image Analysis (L1)
  • Fourier Transform
    • Basic image processing in the fourier domain
    • Convolution
• Sampling <= FT (L1)
  • Aliasing
• Interpolation (L2)
  • perfect reconstruction using sinc
  • truncation artifacts <= FT
  • other interpolation kernels
    • nearest
    • linear
    • cubic
    • b-spline
  • bi/trilinear

Applications

• cardio-vascular disease (L3) <= MPR/CPR
  • Stenosis
  • Aneurysms
• Virtual colonoscopy (L5) <= VolVis
• Blood Flow Analysis. (L6) <= FlowVis
• Brain/Connectome Analysis (L7) <= Tensor Vis

Modalities (L3,6)

• X-Ray (L3)
• CT (L3)
  • Reconstruction <= FT
  • Hounsfield Units
• MRI (L6)
  • K-Space <= FT
  • DW MRI

Volume Visualization (L2-5)

• mpr/cpr (L3)
  • Application: Angiography/CVD
• marching squares/cubes (L2)
  • Phong shading
  • gradient
• DVR (L3-5)
  • MPR
  • Compositing
  • Transfer functions
  • Pre/Post classification
  • Illustrative
  • Application: virtual colonoscopy

Vector Field Visualization (L6)

• Vector Field Integration
  • streamlines/pathlines/streaklines
  • integration methods (Euler/RK)
• Application: Blood flow w/ PC-MRI

Diffusion Tensor Visualization (L7)

• scalar fields (fractional anisotropy ...)
• glyphs
• tensor lines
• Application: brain strucutral connectivity

(Imaging) Cytometry

• high-dimensional data
• visualization of hd data
  • direct (PCP/SPM)
  • indirect (dimensionality reduction)
• Application: immunology research, immunotherapy