Progressive Minimal Path Method for Segmentation of 2D and 3D Line Structures
- Authors
- Liao, Wei; Woerz, Stefan; Kang, Chang-Ki; Cho, Zang-Hee; Rohr, Karl
- Issue Date
- Mar-2018
- Publisher
- IEEE COMPUTER SOC
- Keywords
- Minimal paths; fast marching; dynamic speed function; segmentation of line structures; object detection
- Citation
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.40, no.3, pp.696 - 709
- Journal Title
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Volume
- 40
- Number
- 3
- Start Page
- 696
- End Page
- 709
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/4030
- DOI
- 10.1109/TPAMI.2017.2691709
- ISSN
- 0162-8828
- Abstract
- We propose a novel minimal path method for the segmentation of 2D and 3D line structures. Minimal path methods perform propagation of a wavefront emanating from a start point at a speed derived from image features, followed by path extraction using backtracing. Usually, the computation of the speed and the propagation of the wave are two separate steps, and point features are used to compute a static speed. We introduce a new continuous minimal path method which steers the wave propagation progressively using dynamic speed based on path features. We present three instances of our method, using an appearance feature of the path, a geometric feature based on the curvature of the path, and a joint appearance and geometric feature based on the tangent of the wavefront. These features have not been used in previous continuous minimal path methods. We compute the features dynamically during the wave propagation, and also efficiently using a fast numerical scheme and a low-dimensional parameter space. Our method does not suffer from discretization or metrication errors. We performed qualitative and quantitative evaluations using 2D and 3D images from different application areas.
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