Paper
24 February 2012 Motion compensation of ultrasonic perfusion images
Sebastian Schäfer, Kim Nylund, Odd H. Gilja, Klaus D. Tönnies
Author Affiliations +
Abstract
Contrast-enhanced ultrasound (CEUS) is a rapid and inexpensive medical imaging technique to assess tissue perfusion with a high temporal resolution. It is composed of a sequence with ultrasound brightness values and a contrast sequence acquired simultaneously. However, the image acquisition is disturbed by various motion influences. Registration is needed to obtain reliable information of spatial correspondence and to analyze perfusion characteristics over time. We present an approach to register an ultrasonography sequence by using a feature label map. This label map is generated from the b-mode data sequence by a Markov-Random-Field (MRF) based analysis, where each location is assigned to one of the user-defined regions according to its statistical parameters. The MRF reduces the chance that outliers are represented in the label map and provides stable feature labels over the time frames. A registration consisting of rigid and non-rigid transformations is determined consecutively using the generated label map of the respective frames for similarity calculation. For evaluation, the standard deviation within specific regions in intestinal CEUS images has been measured before and after registration resulting in an average decrease of 8.6 %. Additionally, this technique has proven to be more robust against noise influence compared to similarity calculation based on image intensities only. The latter leads only to 7.6 % decrease of the standard deviation.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sebastian Schäfer, Kim Nylund, Odd H. Gilja, and Klaus D. Tönnies "Motion compensation of ultrasonic perfusion images", Proc. SPIE 8320, Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy, 83200X (24 February 2012); https://doi.org/10.1117/12.911236
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Cited by 2 scholarly publications.
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KEYWORDS
Image registration

Magnetorheological finishing

Ultrasonography

Tissues

Data acquisition

Image segmentation

Medical imaging

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