The Global Track Concept for Assessment of Engaging Hill-Sachs Defects in Anterior Shoulder Instability.

Background: The glenoid track concept is used to determine preoperatively whether a Hill-Sachs defect is engaging or not. Currently, the glenoid track concept relies on measurements of bony structures as well as on the confines and elasticity of the rotator cuff as a reference point, which varies extensively among individuals and therefore limits the reliability and accuracy of this concept.

Purpose: To evaluate the reliability of the global track concept, which determines the angular distance of the Hill-Sachs defect from the center of the articular surface of the humeral head as a new reference point with the help of an automated image analysis software and 3-dimensional analysis of the humeral head.

Reliability of Manual Measurements Versus Semiautomated Software for Glenoid Bone Loss Quantification in Patients With Anterior Shoulder Instability.

Background: The presence of glenoid bone defects is indicative in the choice of treatment for patients with anterior shoulder instability. In contrast to traditional linear- and area-based measurements, techniques such as the consideration of glenoid concavity have been proposed and validated.

Purpose: To compare the reliability of linear (1-dimensional [1D]), area (2-dimensional [2D]), and concavity (3-dimensional [3D]) measurements to quantify glenoid bone loss performed manually and to analyze how automated measurements affect reliability.

Femur reconstruction in 3D ultrasound for orthopedic surgery planning.

Purpose: Derotation varisation osteotomy of the proximal femur in pediatric patients usually relies on 2-dimensional X-ray imaging, as CT and MRI still are disadvantageous when applied in small children either due to a high radiation exposure or the need of anesthesia. This work presents a radiation-free non-invasive tool to 3D-reconstruct the femur surface and measure relevant angles for orthopedic diagnosis and surgery planning from 3D ultrasound scans instead.

Methods: Multiple tracked ultrasound recordings are segmented, registered and reconstructed to a 3D femur model allowing for manual measurements of caput-collum-diaphyseal (CCD) and femoral anteversion (FA) angles.

Correction to: On the reproducibility of expert-operated and robotic ultrasound acquisitions.

The original version of this article unfortunately contained a mistake.

Robotic ultrasound-guided facet joint insertion.

Purpose: Facet joint insertion is a common treatment of chronic pain in the back and spine. This procedure is often performed under fluoroscopic guidance, where the staff's repetitive radiation exposure remains an unsolved problem. Robotic ultrasound (rUS) has the potential to reduce or even eliminate the use of radiation by using ultrasound with a robotic-guided needle insertion.

On the reproducibility of expert-operated and robotic ultrasound acquisitions.

Purpose: We present the evaluation of the reproducibility of measurements performed using robotic ultrasound imaging in comparison with expert-operated sonography. Robotic imaging for interventional procedures may be a valuable contribution, but requires reproducibility for its acceptance in clinical routine. We study this by comparing repeated measurements based on robotic and expert-operated ultrasound imaging.

3D ultrasound registration-based visual servoing for neurosurgical navigation.

Purpose: We present a fully image-based visual servoing framework for neurosurgical navigation and needle guidance. The proposed servo-control scheme allows for compensation of target anatomy movements, maintaining high navigational accuracy over time, and automatic needle guide alignment for accurate manual insertions.

Method: Our system comprises a motorized 3D ultrasound (US) transducer mounted on a robotic arm and equipped with a needle guide.

Towards MRI-Based Autonomous Robotic US Acquisitions: A First Feasibility Study.

Robotic ultrasound has the potential to assist and guide physicians during interventions. In this work, we present a set of methods and a workflow to enable autonomous MRI-guided ultrasound acquisitions. Our approach uses a structured-light 3D scanner for patient-to-robot and image-to-patient calibration, which in turn is used to plan 3D ultrasound trajectories.

Dual-robot ultrasound-guided needle placement: closing the planning-imaging-action loop.

Purpose: Precise needle placement is an important task during several medical procedures. Ultrasound imaging is often used to guide the needle toward the target region in soft tissue. This task remains challenging due to the user's dependence on image quality, limited field of view, moving target, and moving needle.

Multimodal image-guided prostate fusion biopsy based on automatic deformable registration.

Purpose: Transrectal ultrasound (TRUS)-guided random prostate biopsy is, in spite of its low sensitivity, the gold standard for the diagnosis of prostate cancer. The recent advent of PET imaging using a novel dedicated radiotracer, [Formula: see text]-labeled prostate-specific membrane antigen (PSMA), combined with MRI provides improved pre-interventional identification of suspicious areas. This work proposes a multimodal fusion image-guided biopsy framework that combines PET-MRI images with TRUS, using automatic segmentation and registration, and offering real-time guidance.

3D velocity field and flow profile reconstruction from arbitrarily sampled Doppler ultrasound data.

With the need for adequate analysis of blood flow dynamics, different maging modalities have been developed to measure varying blood velocities over time. Due to its numerous advantages, Doppler ultrasound sonography remains one of the most widely used techniques in clinical routine, but requires additional preprocessing to recover 3D velocity information. Despite great progress in the last years, recent approaches do not jointly consider spatial and temporal variation in blood flow.

Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals.

Diagnosis and treatment of dilated cardiomyopathy (DCM) is challenging due to a large variety of causes and disease stages. Computational models of cardiac electrophysiology (EP) can be used to improve the assessment and prognosis of DCM, plan therapies and predict their outcome, but require personalization. In this work, we present a data-driven approach to estimate the electrical diffusivity parameter of an EP model from standard 12-lead electrocardiograms (ECG).

Fast data-driven calibration of a cardiac electrophysiology model from images and ECG.

Recent advances in computational electrophysiology (EP) models make them attractive for clinical use. We propose a novel data-driven approach to calibrate an EP model from standard 12-lead electrocardiograms (ECG), which are in contrast to invasive or dense body surface measurements widely available in clinical routine. With focus on cardiac depolarization, we first propose an efficient forward model of ECG by coupling a mono-domain, Lattice-Boltzmann model of cardiac EP to a boundary element formulation of body surface potentials.