Title
A Multiscale Ray-Shooting Model for Termination Detection of Tree-Like Structures in Biomedical Images.
Abstract
Digital reconstruction (tracing) of tree-like structures, such as neurons, retinal blood vessels and bronchi, from volumetric images and 2D images is very important to biomedical research. Many existing reconstruction algorithms rely on a set of good seed points. 2D or 3D terminations are good candidates for such seed points. In this paper, we propose an automatic method to detect terminations for tree-like structures based on a multiscale ray-shooting model and a termination visual prior. The multiscale ray-shooting model detects 2D terminations by extracting and analyzing the multiscale intensity distribution features around a termination candidate. The range of scale is adaptively determined according to the local neurite diameter estimated by the Rayburst sampling algorithm in combination with the gray-weighted distance transform (GWDT). The termination visual prior is based on a key observation - when observing a 3D termination from three orthogonal directions without occlusion, we can recognize it in at least two views. Using this prior with the multiscale ray-shooting model, we can detect 3D terminations with high accuracies. Experiments on 3D neuron image stacks, 2D neuron images, 3D bronchus image stacks and 2D retinal blood vessel images exhibit average precision and recall rates of 87.50% and 90.54% respectively. The experimental results confirm that the proposed method outperforms other state-of-the-art termination detection methods.
Year
DOI
Venue
2019
10.1109/TMI.2019.2893117
IEEE transactions on medical imaging
Keywords
Field
DocType
Three-dimensional displays,Neurons,Two dimensional displays,Biomedical imaging,Adaptation models,Visualization,Biological system modeling
Computer vision,Visualization,Medical imaging,Precision and recall,Distance transform,Artificial intelligence,Sampling (statistics),Digital reconstruction,Retinal blood vessels,Mathematics,Tracing
Journal
Volume
Issue
ISSN
38
8
1558-254X
Citations 
PageRank 
References 
1
0.37
0
Authors
4
Name
Order
Citations
PageRank
Min Liu1239.55
Weixun Chen2104.58
Chao Wang3895190.04
Hanchuan Peng43930182.27