Tissue Motion Estimation and Correction in Super Resolution Imaging

Jørgen Arendt Jensen, Sofie B. Andersen, Carlos A. Villagomez Hoyos, Kristoffer L. Hansen, Charlotte M. Sørensen, Michael Bachmann Nielsen

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Abstract

Super resolution imaging (SRI) can attain resolutions in the 10-20 µm range to visualize capillary circulation. It requires completely stationary interrogated tissue during the 3- to 10-minute acquisition, which is not obtainable for live animals apart from in the brain. All other organs move due to respiration, heart pulsation, and muscle activity. SRI can, thus, only be obtained with proper compensation for these motions. A method for full 2D tissue motion estimation is suggested, and it is shown how this motion compensation can restore SRI of small vessels in a rat kidney. A BK 5000 scanner was used with a X18L5 transducer (BK Medical). B-mode and contrast pulse sequence images were acquired with an MI of 0.2 at a 54 Hz frame rate for 10 min. The left kidney of a male Sprague-Dawley rat was scanned during laparotomy. A 1:10 diluted SonoVue contrast agent (Bracco) was injected through a jugular vein catheter at 100 µl/min. Envelope B-mode data were used for 2D tissue speckle tracking with sub-pixel precision in a central region of the kidney for axial and lateral motion estimation relative to a reference frame. The three motion components from the rat’s forced ventilation, heart beat, and residual muscular motion were isolated by using the harmonics of the different motion frequencies (breathing 71 bpm, heart 280-350 bpm, residual: other frequencies). The precision of the motion was found by aligning signals across cycles and thereby estimating the mean standard deviation. The motion signal was used for compensating the position of the individual bubble locations back to that of the reference frame to remove motion. Estimated peak motions were: Heart: Axial: 1.2±0.079µm, Lateral: 7±0.99µm, Breathing Ax: 8 ± 0.22µm, Lat: 79 ± 1.64µm, and Residual: Ax: 42 µm, Lat: 110 µm. The estimation is, thus, sufficiently accurate to correct shifts down to the 10 µm capillary level. A motion-corrected image compared to a non-corrected image show small vascular structures in the cortex, which are impossible to separate in the unprocessed image, but can be clearly identified in the motioncorrected image. This demonstrates that motion correction in 2D can enhance SRI quality.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE International Ultrasonics Symposium
PublisherIEEE
Publication date2019
Pages1107-1110
ISBN (Electronic)978-1-7281-4596-9
DOIs
Publication statusPublished - 2019
Event2019 IEEE International Ultrasonics Symposium - SEC Glasgow, Glasgow, United Kingdom
Duration: 6 Oct 20199 Oct 2019
http://attend.ieee.org/ius-2019/

Conference

Conference2019 IEEE International Ultrasonics Symposium
LocationSEC Glasgow
CountryUnited Kingdom
CityGlasgow
Period06/10/201909/10/2019
Internet address

Cite this

Jensen, J. A., Andersen, S. B., Hoyos, C. A. V., Hansen, K. L., Sørensen, C. M., & Nielsen, M. B. (2019). Tissue Motion Estimation and Correction in Super Resolution Imaging. In Proceedings of 2019 IEEE International Ultrasonics Symposium (pp. 1107-1110). IEEE. https://doi.org/10.1109/ULTSYM.2019.8925632