Liver motion estimation and prediction during free-breathing from 2D ultrasound images can substantially reduce the in-plane motion uncertainty and hence treatment margins. Employing an accurate tracking method while avoiding non-linear temporal prediction would be favorable. This approach has the potential to shorten treatment time compared to breath-hold and gated approaches, and increase treatment efficiency and safety.

Objectives A new ultrasound‐based device is proposed to measure the patient‐specific pelvic tilt in different daily positions. The aim of this study was to assess the accuracy of this device as well as the intraobserver and interobserver precisions. Methods The accuracy was assessed by performing several tilt measurements with the device on a testing mechanical bench. The error was defined as the difference between the tilt measured with the device and the tilt provided by this test bench. Three physicians, a novice, an intermediate, and an expert user, were also asked to perform 10 measurements on 3 healthy volunteers with low, medium, and high body mass indices to analyze the intraobserver and interobserver precisions. These 10 measurements were performed in the standing, sitting, and supine positions. Results The mean accuracy of the device ± SD was 1.1° ± 0.7° (range, 0°–4.0°). The interobserver and intraobserver precisions were excellent whatever the body mass index and good to excellent according to the positions. There was no learning curve, and the time required to complete the measurements was approximately 5 minutes. Conclusions This study presents an accurate and precise noninvasive device for measurement of the pelvic tilt in different positions.

The risk of dislocation after THA reportedly is minimized if the acetabular implant is oriented at 45°i nclination and 15°anteversion with respect to the anterior pelvic plane. This reference plane now is used in computerassisted protocols. However, this static approach may lead to postoperative instability because the dynamic variations of the pelvis influence effective cup orientation and are not taken into account in this approach. We propose an ultrasound tool to register the preoperative dynamics of the pelvis for THA planning during computer-assisted surgery. To assess this pelvic behavior and its consequences on implant orientation, we tested a new 2.5-dimensional ultrasound-based approach. The pelvic flexion was registered in sitting, standing, and supine positions in 20 subjects. The mean values were -25.2°± 5.8°(standard deviation), 2.4°± 5.1°, and 6.8°± 3.5°, respectively. The mean functional anteversion varied by 26°and the mean functional inclination by 12°depending on the pelvic flexion. We therefore recommend including dynamic pelvic behavior to minimize dislocation risk. The notion of a safe zone should be revisited and extended to include changes with activity.

The FCN-based approach outperforms the CPS algorithm, and the obtained RMSE is similar to the manual segmentation uncertainty.

In this paper, we present a real-time approach that allows tracking deformable structures in 3D ultrasound sequences. Our method consists in obtaining the target displacements by combining robust dense motion estimation and mechanical model simulation. We perform evaluation of our method through simulated data, phantom data, and real-data. Results demonstrate that this novel approach has the advantage of providing correct motion estimation regarding different ultrasound shortcomings including speckle noise, large shadows and ultrasound gain variation. Furthermore, we show the good performance of our method with respect to state-of-the-art techniques by testing on the 3D databases provided by MICCAI CLUST'14 and CLUST'15 challenges.

In this paper, we present a novel approach for tracking a deformable anatomical target within 3D ultrasound volumes. Our method is able to estimate deformations caused by the physiological motions of the patient. The displacements of moving structures are estimated from an intensity-based approach combined with a physically-based model and has therefore the advantage to be less sensitive to the image noise. Furthermore, our method does not use any fiducial marker and has real-time capabilities. The accuracy of our method is evaluated on real data acquired from an organic phantom. The validation is performed on different types of motions comprising rigid and non-rigid motions. Thus, our approach opens novel possibilities for computer-assisted interventions where deformable organs are involved.

Purpose: A new approach is proposed to localise surgical instruments for Computer Assisted Orthopaedic Surgery (CAOS) that aims at overpassing the limitations of conventional CAOS solutions. This approach relies on both a depth sensor and a 6D pose estimation algorithm. Methods: The Point-Pair Features (PPF) algorithm was used to estimate the pose of a Patient-Specific Instrument (PSI) for Total Knee Arthroplasty (TKA). Four depth sensors have been compared. Three scores have been computed to assess the performances: The Depth Fitting Error (DFE), the Pose Errors, and the Success Rate. Results: The obtained results demonstrate higher performances for the Microsoft Kinect Azure in terms of DFE. The Occipital Structure core shows better behavior in terms of Pose Errors and Success Rate. Conclusion: This comparative study presents the first depth-sensor based solution allowing the intraoperative markerless localization of surgical instruments in orthopedics.

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