chart1. has its origins in:https://all3dp.com/scanallfish-project-turning-worlds-fish-into-3d-scans/
2.ScanAllFish project challenges
So far, the ScanAllFish project has scanned only 600 of these 30,000 species of fish. The reasons are as follows:
Micro-CT is expensive and not widely available
12 hours to complete a single scan
So the scientists decided to wrap multiple fish together for the scanning process. As shown in figure 2:
chart2 (a) Fish binding tags to be scanned (b)12 Tie a fish into a" meat roll" (c) Perform a scan (d) Scan results
Multiple fish are scanned together, and the scan results need to be split to extract the respective results of the different fish. New challenges are posed, such as those shown in subfigure d of figure 2,
The fish can be placed in any direction,
Spatial proximity of the skeletons of different fish ,
The opacity of the rays is similar,
There is no sufficient a priori knowledge of size and shape,
It takes as long as 20 to 40 hours to manually extract the results of the scans of different fish.
3.In order to solve the above challenges, this paper proposes TopoAngler, which combines the computational topology with the viewable bounding surfaces, to perform interactive segmentation on these complex scanned body datasets.
II. System Overview
chart3 system chart a solution.
After reading and downsampling the data, topological analysis is performed, and the results of Join tree and branch decomposition are output, including feature identification and voxel identification.
The user needs to select features at different simplification levels to build meta-features (meta-features)
These meta-features are the output of the post-processing step.
Some of the concepts are sorted out as follows:
Features: connected sub-volume generated after topological analysis, which can be presented at different levels: skeleton, thorax or whole fish.
Meta features: i.e. whole fish. Meta-features are assembled from different layers of features by user interaction. is the final output.
III. hierarchical segmentation
The scalar field data of the microCT is first converted into tetrahedral mesh data, and then the extended connection tree is computed on the tetrahedral mesh (Algorithm: Computing Contour Trees in All Dimensions), and then the tree is decomposed by branching according to the importance measure of each edge in the tree (Algorithm: THE TOPORRERY: computation and presentation of multi-resolution topology).
chart4. Example of tree hierarchy segmentation chart
Requires user input of the number of features presented after simplification
When the number of features is 3, as shown in the above left figure, there are three candidate features ABC
The characteristic number is2 time, edgeBD removed, collaboration withAD The sides converge., constitute a new edgeAE, The final feature is blue with red, as above right chart