Conformal flattening maps for the visualization of vessels

@inproceedings{Zhu2002ConformalFM,
  title={Conformal flattening maps for the visualization of vessels},
  author={Lei Zhu and Steven Haker and Allen R. Tannenbaum},
  booktitle={SPIE Medical Imaging},
  year={2002}
}
In this note, we employ a conformal mapping technique for flattening branching tubular structures for visualization of MRA and CT volumetric vessel imagery. This may be used for the study of possible vessel pathology (cerebral embolism, cerebral thrombosis, or lung nodules near vessels). Our method is based on a discretization of the Laplace-Beltrami operator to flatten a surface onto a planar polygonal region in an angle-preserving manner. 

Angle-preserving mappings for the visualization of multi-branched vessels

We employ a conformal mapping technique to flatten tubular structures with multi-branches for visualization of MRA and CT volumetric vessel imagery. This may be used for the study of possible vessel

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A classification of the existing literature according to the data spaces such maps can be derived from is provided and recommendations for the design of map-like visualizations of the cardiovascular system are offered.

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A linked multi-view approach is chosen, which amongst others integrates a specialized straightened multipath curved planar reformation and a multimodal vessel flattening technique for the visual analysis of PET/CT scans of aortic arches of mice.

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A classification of the existing literature according to the data spaces such maps can be derived from is provided and recommendations for the design of map‐like visualizations of the cardiovascular system are offered.

Evaluation of Artery Visualizations for Heart Disease Diagnosis

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HemoVis is developed, an interactive visualization application for heart disease diagnosis that uses a novel 2D tree diagram representation of coronary artery trees and shows statistically significant results demonstrating that 2D visualizations are more accurate and efficient than 3D representations, and that a perceptually appropriate color map leads to fewer diagnostic mistakes than a rainbow color map.

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Presented at the Workshop on Interactive Medical Image Visualization and Analysis, IMIVA’01, satellite symposia of MICCAI, Utrecht, The Netherlands, September 2001.

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