Journal
NEUROINFORMATICS
Volume 9, Issue 2-3, Pages 279-302Publisher
HUMANA PRESS INC
DOI: 10.1007/s12021-011-9122-1
Keywords
DIADEM; Tree reconstruction; Global optimization; Minimum arborescence; k-MST; Ant colony optimization
Funding
- Swiss National Science Foundation
- MicroNano ERC project
- Spanish Government
Ask authors/readers for more resources
We present a novel probabilistic approach to fully automated delineation of tree structures in noisy 2D images and 3D image stacks. Unlike earlier methods that rely mostly on local evidence, ours builds a set of candidate trees over many different subsets of points likely to belong to the optimal tree and then chooses the best one according to a global objective function that combines image evidence with geometric priors. Since the best tree does not necessarily span all the points, the algorithm is able to eliminate false detections while retaining the correct tree topology. Manually annotated brightfield micrographs, retinal scans and the DIADEM challenge datasets are used to evaluate the performance of our method. We used the DIADEM metric to quantitatively evaluate the topological accuracy of the reconstructions and showed that the use of the geometric regularization yields a substantial improvement.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available