Confidence-Driven Control of an Ultrasound Probe: Target-Specific Acoustic Window Optimization

International audienceWe propose a control framework to optimize the quality of robotic ultrasound imaging while tracking an anatomical target. We use a multitask approach to control the in-plane motion of a convex probe mounted on the end-effector of a robotic arm, based not only on the position of the target in the image, but also on features extracted from an ultrasound confidence map. The resulting control law therefore guarantees a good image quality, while keeping the target aligned with the central ultrasound scan-line. Potential applications of the proposed approach are, for example, teleoperated ultrasound examination, motion compensation for ultrasound-guided interventions , or automatic ultrasound acquisition. We demonstrate our approach with experiments on an ultrasound examination training phantom in motion

Ultrax:An Animated Midsagittal Vocal Tract Display for Speech Therapy

Speech sound disorders (SSD) are the most common communication impairment in childhood, and can hamper social development and learning. Current speech therapy interventions rely predominantly on the auditory skills of the child, as little technology is available to assist in diagnosis and therapy of SSDs. Realtime visualisation of tongue movements has the potential to bring enormous benefit to speech therapy. Ultrasound scanning offers this possibility, although its display may be hard to interpret. Our ultimate goal is to exploit ultrasound to track tongue movement, while displaying a simplified, diagrammatic vocal tract that is easier for the user to interpret. In this paper, we outline a general approach to this problem, combining a latent space model with a dimensionality reducing model of vocal tract shapes. We assess the feasibility of this approach using magnetic resonance imaging (MRI) scans to train a model of vocal tract shapes, which is animated using electromagnetic articulography (EMA) data from the same speaker. Index Terms: Ultrasound, speech therapy, vocal tract visualisation 1

Reference charts for fetal cerebellar vermis height: A prospective cross-sectional study of 10605 fetuses

A prospective cross-sectional study between September 2009 and December 2014 was carried out at ALTAMEDICA Fetal–Maternal Medical Centre, Rome, Italy. Of 25203 fetal biometric measurements, 12167 (48%) measurements of the cerebellar vermis were available. After excluding 1562 (12.8%) measurements, a total of 10605 (87.2%) fetuses were considered and analyzed once only. Parametric and nonparametric quantile regression models were used for the statistical analysis. In order to evaluate the robustness of the proposed reference charts regarding various distributional assumptions on the ultrasound measurements at hand, we compared the gestational age-specific reference curves we produced through the statistical methods used. Normal mean height based on parametric and nonparametric methods were defined for each week of gestation and the regression equation expressing the height of the cerebellar vermis as a function of gestational age was calculated. Finally the correlation between dimension/gestation was measured

Learning Ultrasound Scanning Skills from Human Demonstrations

Recently, the robotic ultrasound system has become an emerging topic owing to the widespread use of medical ultrasound. However, it is still a challenging task to model and to transfer the ultrasound skill from an ultrasound physician. In this paper, we propose a learning-based framework to acquire ultrasound scanning skills from human demonstrations. First, the ultrasound scanning skills are encapsulated into a high-dimensional multi-modal model in terms of interactions among ultrasound images, the probe pose and the contact force. The parameters of the model are learned using the data collected from skilled sonographers' demonstrations. Second, a sampling-based strategy is proposed with the learned model to adjust the extracorporeal ultrasound scanning process to guide a newbie sonographer or a robot arm. Finally, the robustness of the proposed framework is validated with the experiments on real data from sonographers

Overview of bladder heating technology: matching capabilities with clinical requirements.

Moderate temperature hyperthermia (40-45°C for 1 h) is emerging as an effective treatment to enhance best available chemotherapy strategies for bladder cancer. A rapidly increasing number of clinical trials have investigated the feasibility and efficacy of treating bladder cancer with combined intravesical chemotherapy and moderate temperature hyperthermia. To date, most studies have concerned treatment of non-muscle-invasive bladder cancer (NMIBC) limited to the interior wall of the bladder. Following the promising results of initial clinical trials, investigators are now considering protocols for treatment of muscle-invasive bladder cancer (MIBC). This paper provides a brief overview of the devices and techniques used for heating bladder cancer. Systems are described for thermal conduction heating of the bladder wall via circulation of hot fluid, intravesical microwave antenna heating, capacitively coupled radio-frequency current heating, and radiofrequency phased array deep regional heating of the pelvis. Relative heating characteristics of the available technologies are compared based on published feasibility studies, and the systems correlated with clinical requirements for effective treatment of MIBC and NMIBC

Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.Comment: Accepted by Medical Image Analysi

Simultaneous determination of wave speed and arrival time of reflected waves using the pressure-velocity loop

This is the post print version of the article. The official published version can be found at the link below.In a previous paper we demonstrated that the linear portion of the pressure–velocity loop (PU-loop) corresponding to early systole could be used to calculate the local wave speed. In this paper we extend this work to show that determination of the time at which the PU-loop first deviates from linearity provides a convenient way to determine the arrival time of reflected waves (Tr). We also present a new technique using the PU-loop that allows for the determination of wave speed and Tr simultaneously. We measured pressure and flow in elastic tubes of different diameters, where a strong reflection site existed at known distances away form the measurement site. We also measured pressure and flow in the ascending aorta of 11 anaesthetised dogs where a strong reflection site was produced through total arterial occlusion at four different sites. Wave speed was determined from the initial slope of the PU-loop and Tr was determined using a new algorithm that detects the sampling point at which the initial linear part of the PU-loop deviates from linearity. The results of the new technique for detecting Tr were comparable to those determined using the foot-to-foot and wave intensity analysis methods. In elastic tubes Tr detected using the new algorithm was almost identical to that detected using wave intensity analysis and foot-to-foot methods with a maximum difference of 2%. Tr detected using the PU-loop in vivo highly correlated with that detected using wave intensity analysis (r 2 = 0.83, P < 0.001). We conclude that the new technique described in this paper offers a convenient and objective method for detecting Tr, and allows for the dynamic determination of wave speed and Tr, simultaneously

Identifying Visible Tissue in Intraoperative Ultrasound Images during Brain Surgery: A Method and Application

Intraoperative ultrasound scanning is a demanding visuotactile task. It requires operators to simultaneously localise the ultrasound perspective and manually perform slight adjustments to the pose of the probe, making sure not to apply excessive force or breaking contact with the tissue, whilst also characterising the visible tissue. In this paper, we propose a method for the identification of the visible tissue, which enables the analysis of ultrasound probe and tissue contact via the detection of acoustic shadow and construction of confidence maps of the perceptual salience. Detailed validation with both in vivo and phantom data is performed. First, we show that our technique is capable of achieving state of the art acoustic shadow scan line classification - with an average binary classification accuracy on unseen data of 0.87. Second, we show that our framework for constructing confidence maps is able to produce an ideal response to a probe's pose that is being oriented in and out of optimality - achieving an average RMSE across five scans of 0.174. The performance evaluation justifies the potential clinical value of the method which can be used both to assist clinical training and optimise robot-assisted ultrasound tissue scanning