Improving subviral particle tracks in fluoroscopic image sequences by global motion compensation
Automatic detection and tracking of subviral particles in image sequences is an indispensable supportive method for modern medicine research programs. This paper describes the development of a highly adaptable camera-to-world system motion invariant tracking algorithm. A translation compensation is...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2017-09-01
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| Series: | Current Directions in Biomedical Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/cdbme-2017-0044 |
| Summary: | Automatic detection and tracking of subviral particles in image sequences is an indispensable supportive method for modern medicine research programs. This paper describes the development of a highly adaptable camera-to-world system motion invariant tracking algorithm. A translation compensation is obtained by cross correlations. Particles are detected by an implemented existing algorithm. The detected particles are linked by solving a Linear Assignment Problem. For highly stable results the tracks are improved by Kalman filtering. The algorithm is tested on simulated sequences. The results show a great ability for stable tracking. |
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| ISSN: | 2364-5504 |