Total Variation Regularization of Pose Signals with an Application to 3D Freehand Ultrasound.

Three-dimensional freehand imaging techniques are gaining wider adoption due to their ?exibility and cost ef?ciency. Typical examples for such a combination of a tracking system with an imaging device are freehand SPECT or freehand 3D ultrasound. However, the quality of the resulting image data is heavily dependent on the skill of the human operator and on the level of noise of the tracking data. The latter aspect can introduce blur or strong artifacts, which can signi?cantly hamper the interpretation of image data. Unfortunately, the most commonly used tracking systems to date, i.e. optical and electromagnetic, present a trade-off between invading the surgeon's workspace (due to line-of-sight requirements) and higher levels of noise and sensitivity due to the interference of surrounding metallic objects. In this work, we propose a novel approach for total variation regularization of data from tracking systems (which we term pose signals) based on a variational formulation in the manifold of Euclidean transformations. The performance of the proposed approach was evaluated using synthetic data as well as real ultrasound sweeps executed on both a Lego phantom and human anatomy, showing signi?cant improvement in terms of tracking data quality and compounded ultrasound images. Source code can be found at https://github.com/IFL-CAMP/pose_regularization.

Use the force: deformation correction in robotic 3D ultrasound.

PURPOSE: Ultrasound acquisitions are typically affected by deformations due to the pressure applied onto the contact surface. While a certain amount of pressure is necessary to ensure good acoustic coupling and visibility of the anatomy under examination, the caused deformations hinder accurate localization and geometric analysis of anatomical structures. These complications have even greater impact in case of 3D ultrasound scans as they limit the correct reconstruction of acquired volumes. METHODS: In this work, we propose a method to estimate and correct the induced deformation based solely on the tracked ultrasound images and information about the applied force. This is achieved by modeling estimated displacement fields of individual image sequences using the measured force information. By representing the computed displacement fields using a graph-based approach, we are able to recover a deformation-less 3D volume. RESULTS: Validation is performed on 30 in vivo human datasets acquired using a robotic ultrasound framework. Compared to ground truth, the presented deformation correction shows errors of [Formula: see text] for an applied force of 5 N at a penetration depth of 55 mm. CONCLUSION: The proposed technique allows for the correction of deformations induced by the transducer pressure in entire 3D ultrasound volumes. Our technique does not require biomechanical models, patient-specific assumptions or information about the tissue properties; it can be employed based on the information from readily available robotic ultrasound platforms.

SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode.

PURPOSE: Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms. METHODS: With SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time. RESULTS: The pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time. CONCLUSIONS: Our software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.

Acoustic window planning for ultrasound acquisition.

Autonomous robotic ultrasound has recently gained considerable interest, especially for collaborative applications. Existing methods for acquisition trajectory planning are solely based on geometrical considerations, such as the pose of the transducer with respect to the patient surface. PURPOSE: This work aims at establishing acoustic window planning to enable autonomous ultrasound acquisitions of anatomies with restricted acoustic windows, such as the liver or the heart. METHODS: We propose a fully automatic approach for the planning of acquisition trajectories, which only requires information about the target region as well as existing tomographic imaging data, such as X-ray computed tomography. The framework integrates both geometrical and physics-based constraints to estimate the best ultrasound acquisition trajectories with respect to the available acoustic windows. We evaluate the developed method using virtual planning scenarios based on real patient data as well as for real robotic ultrasound acquisitions on a tissue-mimicking phantom. RESULTS: The proposed method yields superior image quality in comparison with a naive planning approach, while maintaining the necessary coverage of the target. CONCLUSION: We demonstrate that by taking image formation properties into account acquisition planning methods can outperform naive plannings. Furthermore, we show the need for such planning techniques, since naive approaches are not sufficient as they do not take the expected image quality into account.