CNF:Weighted Mesh To Image: Difference between revisions
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Comparison Metrics: | Comparison Metrics: | ||
# Mean Weighted pixel value difference | # Mean Weighted pixel value difference | ||
## | ## [[File:MeanWeightedPixelValueFormula.png|500px|File:MeanWeightedPixelValueFormula.png]] | ||
# Average Hausdorff Distance (itk filter) | # Average Hausdorff Distance (itk filter) | ||
# Similarity Index (itk filter) | # Similarity Index (itk filter) | ||
Revision as of 11:14, 10 June 2020
Repository
Code
Summer 2020
Create a new image using the weights of:
- k-nearest-neighbors points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, neighbor-point[i]) ^ power.
- cell points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, cell-point[i]) ^ power.
- Note: If the pixel point is not inside a cell, then the algorithm `1` will be used.
- the intersection set of k-nearest-neighbors points and cell points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, intersection-point[i]) ^ power.
- Note 1: If the Intersection set is empty, then the algorithm `2` will be used.
- Note 2: If the pixel point is not inside a cell, then the algorithm `1` will be used.
- cell points as values in a weighted-mean, were weight[i] = probe-value[i] based on the location of each pixel point inside a cell. Probing values are result of FindCell function.
- Note: If the pixel point is not inside a cell, then the algorithm `1` will be used.
Comparison Metrics: