Evidence map›Paper›PMID 35704237›Full record

ArticleInternational journal of computer assisted radiology and surgery2022

Spatiotemporal reconstruction method of carotid artery ultrasound from freehand sonography.

Hanying Liang, Guochen Ning, Shangqi Dai, Longfei Ma, Jianwen Luo, Xinran Zhang, Hongen Liao

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Article in International journal of computer assisted radiology and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Hanying LiangDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Guochen NingDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Shangqi DaiDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Longfei MaDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Jianwen LuoDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Xinran ZhangDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Hongen LiaoDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China. liao@tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-3847-9347

Funding

Beijing Municipal Natural Science Foundation 7212202Beijing Municipal Natural Science Foundation L192013China Postdoctoral Science Foundation 2021M701928National Natural Science Foundation of China 81901844National Natural Science Foundation of China 82027807
6 · The paper itself

Abstract

purpose4D reconstruction based on radiation-free ultrasound can provide valuable information about the anatomy. Current 4D US technologies are either faced with limited field-of-view (FoV), technical complications, or cumbersome setups. This paper proposes a spatiotemporal US reconstruction framework to enhance its ability to provide dynamic structure information.

methodsWe propose a spatiotemporal US reconstruction framework based on freehand sonography. First, a collecting strategy is presented to acquire 2D US images in multiple spatial and temporal positions. A morphology-based phase extraction method after pose correction is presented to decouple the compounding image variations. For temporal alignment and reconstruction, a robust kernel regression model is established to reconstruct images in arbitrary phases. Finally, the spatiotemporal reconstruction is demonstrated in the form of 4D movies by integrating the US images according to the tracked poses and estimated phases.

resultsQuantitative and qualitative experiments were conducted on the carotid US to validate the feasibility of the proposed pipeline. The mean phase localization and heart rate estimation errors were 0.07 ± 0.04 s and 0.83 ± 3.35 bpm, respectively, compared with cardiac gating signals. The assessment of reconstruction quality showed a low RMSE (<0.06) between consecutive images. Quantitative comparisons of anatomy reconstruction from the generated US volumes and MRI showed an average surface distance of 0.39 ± 0.09 mm on the common carotid artery and 0.53 ± 0.05 mm with a landmark localization error of 0.60 ± 0.18 mm on carotid bifurcation.

conclusionA novel spatiotemporal US reconstruction framework based on freehand sonography is proposed that preserves the utility nature of conventional freehand US. Evaluations on in vivo datasets indicated that our framework could achieve acceptable reconstruction performance and show potential application value in the US examination of dynamic anatomy.

Indexed as

Imaging, Three-DimensionalMagnetic Resonance ImagingAlgorithmsCarotid ArteriesHumansImage Processing, Computer-AssistedUltrasonographyUltrasonography, DopplerFreehand sonographyPhase estimationSpatiotemporal reconstructionUltrasound

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.