Configurable real-time motion estimation for medical imaging: application to X-ray and ultrasound
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Motion estimation is a key building block of image processing pipelines in many different contexts, ranging from efficient coding of video sequences in the consumer electronics domain (TV, DVD, BD) to professional medical applications. Many block-matching approaches have been proposed in the literature for motion detection and compensation in general, including both lossless and lossy algorithms. However, in real-time medical imaging applications, characterized by high frame rates, the needs for low latency and jitter, accuracy and robustness against noise are quite difficult to achieve with standard block-matching methods. We introduce a new hybrid image processing approach to block-matching that takes advantage of both types of algorithms (lossless and lossy), adapts to the image content and noise, and provides high flexibility for the speed/accuracy tradeoff. The presented approach has been successfully tested on interventional X-ray fluoroscopy and cardiac ultrasound images sequences.
KeywordsMotion estimation Medical imaging Block matching Configurable speedup Content-based classification
The authors would like to gratefully acknowledge the continuous support from the “Image Processing” group at the St. Petersburg State Polytechnic University and the supervision of this work by Assistant Professor M. Bolsunovskaya—as well as the support, hosting, and collaboration by the Philips Research Medisys group in Suresnes, headed by Nicolas Villain.
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