Moment curves

We define a transfer function based on the first and second statistical moments. We consider the evolution of the mean and variance with respect to a growing neighborhood around a voxel. This evolution defines a curve in 3D for which we identify important trends and project it back to 2D. The result...

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Vydáno v:2009 IEEE Pacific Visualization Symposium s. 201 - 208
Hlavní autoři: Patel, D., Haidacher, M., Balabanian, J.-P., Groller, E.M.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.04.2009
Témata:
Computed tomography
Computer graphics
Histograms
I.4.10 [Image Processing]: Image Representation-Statistical
I.4.10 [Image Processing]: Image Representation-Volumetric
I.4.6 [Image Processing]: Segmentation-Pixel classification
I.4.7 [Image Processing]: Feature Measurement-Feature representation
Image processing
Image segmentation
Informatics
Material properties
Noise robustness
Transfer functions
Volume measurement
ISBN:1424444047, 9781424444045
ISSN:2165-8765
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Shrnutí:We define a transfer function based on the first and second statistical moments. We consider the evolution of the mean and variance with respect to a growing neighborhood around a voxel. This evolution defines a curve in 3D for which we identify important trends and project it back to 2D. The resulting 2D projection can be brushed for easy and robust classification of materials and material borders. The transfer function is applied to both CT and MR data.
ISBN:1424444047
9781424444045
ISSN:2165-8765
DOI:10.1109/PACIFICVIS.2009.4906857