Progressive minimal path method for segmentation of 2D and 3D line structures
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...
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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2018
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| In: |
IEEE transactions on pattern analysis and machine intelligence
Year: 2017, Volume: 40, Issue: 3, Pages: 696-709 |
| ISSN: | 1939-3539 |
| DOI: | 10.1109/TPAMI.2017.2691709 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1109/TPAMI.2017.2691709 Verlag, Volltext: https://ieeexplore.ieee.org/document/7893744/ 
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| Author Notes: | W. Liao, S. Wörz, C. Kang, Z. Cho, and K. Rohr |
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| 245 | 1 | 0 | |a Progressive minimal path method for segmentation of 2D and 3D line structures |c W. Liao, S. Wörz, C. Kang, Z. Cho, and K. Rohr |
| 264 | 1 | |c 2018 | |
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| 500 | |a Gesehen am 12.09.2018 | ||
| 520 | |a 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. | ||
| 534 | |c 2017 | ||
| 650 | 4 | |a 2D line structures | |
| 650 | 4 | |a 3D line structures | |
| 650 | 4 | |a appearance feature | |
| 650 | 4 | |a Bridges | |
| 650 | 4 | |a continuous minimal path method | |
| 650 | 4 | |a continuous minimal path methods | |
| 650 | 4 | |a discretization errors | |
| 650 | 4 | |a dynamic speed function | |
| 650 | 4 | |a fast marching | |
| 650 | 4 | |a fast numerical scheme | |
| 650 | 4 | |a feature extraction | |
| 650 | 4 | |a Feature extraction | |
| 650 | 4 | |a geometric feature | |
| 650 | 4 | |a image features | |
| 650 | 4 | |a image reconstruction | |
| 650 | 4 | |a image segmentation | |
| 650 | 4 | |a Image segmentation | |
| 650 | 4 | |a low-dimensional parameter space | |
| 650 | 4 | |a metrication errors | |
| 650 | 4 | |a Minimal paths | |
| 650 | 4 | |a object detection | |
| 650 | 4 | |a path extraction | |
| 650 | 4 | |a path features | |
| 650 | 4 | |a point features | |
| 650 | 4 | |a progressive minimal path method | |
| 650 | 4 | |a Propagation | |
| 650 | 4 | |a Satellites | |
| 650 | 4 | |a segmentation of line structures | |
| 650 | 4 | |a Three-dimensional displays | |
| 650 | 4 | |a Two dimensional displays | |
| 650 | 4 | |a wave propagation | |
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