Computer vision (CV) libraries such as OpenCV provide versatile algorithms for object tracking. We demonstrate the feasibility of out-of-the-box object trackers in different dynamic MR imaging scenarios. In contrast to specialized detection and registration algorithms, the generic implementation of object trackers enables targeting of different and challenging organs during respiratory motion, including the heart, liver and kidney. Apart from post-processing, fast algorithm and implementation allowed for application in our online and prospective motion compensation pipeline. By leveraging these open source libraries, MR applications can benefit from both the current powerful library and the continuous developments by the CV community.
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