Image-Based Methods for Phase Estimation, Gating, and Temporal Superresolution of Cardiac Ultrasound

Spatiotemporal reconstruction method of carotid artery ultrasound from freehand sonography

PURPOSE

4D 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.

METHODS

We 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.

RESULTS

Quantitative 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.

CONCLUSION

A 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.

Separated Respiratory Phases for In Vivo Ultrasonic Thermal Strain Imaging

Thermal strain imaging (TSI) uses echo shifts in ultrasonic B-scan images to estimate changes in temperature which is of great values for thermotherapies. However, for in vivo applications, it is difficult to overcome the artifacts and errors arising from physiological motions. Here, a respiration separated TSI (RS-TSI) method is proposed, which can be considered as carrying out TSI in each of the exhalation and inhalation phases and then combining the results. Normalized cross correlation (NXcorr) coefficient between RF images along the timeline are used to extract the respiratory frequency, after which reference frames are selected to identify the exhalation and inhalation phases, and the two phases are divided quasi-periodically. RF images belonging to both phases are selected by applying NXcorr thresholds, and motion compensation together with a second frame selection helps to obtain two finely matched image sequences. After TSI calculations for each phase, the two processes are merged into one through extrapolation and interphase averaging. Compared to TSI based on dynamic frame selection (DFS), RS-TSI ensures that frames are selected during both the exhalation and inhalation phases while setting the frame selection range according to the respiratory frequency helps to improve motion compensation. The temporal intervals of TSI output are approximately half that employing DFS.