Abstract
The development of vessels can provide important information about the growth status of animal embryos. It is, therefore, important to automatically locate the deformed vessel branches from the embryo images. However, very few vessel detectors can accurately locate all vessel branches when the captured images are low quality and the implied vessel shapes are complex. In this study, a new framework consisting of vessel region extraction and snake shape optimisation is proposed. The main contribution in this detector is a novel open snake model based on the global guidance field and deformation template initialisation. Experimental results on a specific application of an embryo vessel database [Database and source codes: https:// github.com/wcxie/Egg-embryro-vessel-location/.] demonstrate that the proposed algorithm not only locates the vessel shape properly but also obtains the orientations of embryo vessel branches accurately. Comparison to traditional guidance fields and the active appearance model illustrates the effectiveness and competitiveness of the proposed model.
Original language | English |
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Pages (from-to) | 129-137 |
Number of pages | 9 |
Journal | IET Computer Vision |
Volume | 12 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Mar 2018 |
Externally published | Yes |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition