Korsgaardsutherland4501

74% mean average precision for the detection task and 98.77% accuracy for the classification task. Their model can reflect the detailed circumstance of the gastroscopy examination process, which shows application potential in improving the quality of examinations.High-intensity focused ultrasound (HIFU) therapy represents an image-guided and non-invasive surgical approach to treat uterine fibroid. During the HIFU operation, it is challenging to obtain the real-time and accurate lesion contour automatically in ultrasound (US) video. The current intraoperative image processing is completed manually or semi-automatic. In this Letter, the authors propose a morphological active contour without an edge-based model to obtain accurate real-time and non-rigid US lesion contour. Firstly, a targeted image pre-processing procedure is applied to reduce the influence of inadequate image quality. Then, an improved morphological contour detection method with a customised morphological kernel is harnessed to solve the low signal-to-noise ratio of HIFU US images and obtain an accurate non-rigid lesion contour. A more reasonable lesion tracking procedure is proposed to improve tracking accuracy especially in the case of large displacement and incomplete lesion area. The entire framework is accelerated by the GPU to achieve a high frame rate. Finally, a non-rigid, real-time and accurate lesion contouring for intraoperative US video is provided to the doctor. The proposed procedure could reach a speed of more than 30 frames per second in general computer and a Dice similarity coefficient of 90.67% and Intersection over Union of 90.14%.The correct placement of needles is decisive for the success of many minimally-invasive interventions and therapies. These needle insertions are usually only guided by radiological imaging and can benefit from additional navigation support. Augmented reality (AR) is a promising tool to conveniently provide needed information and may thus overcome the limitations of existing approaches. To this end, a prototypical AR application was developed to guide the insertion of needles to spinal targets using the mixed reality glasses Microsoft HoloLens. The system's registration accuracy was attempted to measure and three guidance visualisation concepts were evaluated concerning achievable in-plane and out-of-plane needle orientation errors in a comparison study. Results suggested high registration accuracy and showed that the AR prototype is suitable for reducing out-of-plane orientation errors. Limitations, like comparatively high in-plane orientation errors, effects of the viewing position and missing image slices indicate potential for improvement that needs to be addressed before transferring the application to clinical trials.Image-based surgical instrument tracking in robot-assisted surgery is an active and challenging research area. Having a real-time knowledge of surgical instrument location is an essential part of a computer-assisted intervention system. Tracking can be used as visual feedback for servo control of a surgical robot or transformed as haptic feedback for surgeon-robot interaction. In this Letter, the authors apply a multi-domain convolutional neural network for fast 2D surgical instrument tracking considering the application for multiple surgical tools and use a focal loss to decrease the effect of easy negative examples. They further introduce a new dataset based on m2cai16-tool and their cadaver experiments due to the lack of established public surgical tool tracking dataset despite significant progress in this field. Their method is evaluated on the introduced dataset and outperforms the state-of-the-art real-time trackers.Depth estimation plays an important role in vision-based laparoscope surgical navigation systems. Most learning-based depth estimation methods require ground truth depth or disparity images for training; however, these data are difficult to obtain in laparoscopy. The authors present an unsupervised learning depth estimation approach by fusing traditional stereo knowledge. The traditional stereo method is used to generate proxy disparity labels, in which unreliable depth measurements are removed via a confidence measure to improve stereo accuracy. The disparity images are generated by training a dual encoder-decoder convolutional neural network from rectified stereo images coupled with proxy labels generated by the traditional stereo method. A principled mask is computed to exclude the pixels, which are not seen in one of views due to parallax effects from the calculation of loss function. Moreover, the neighbourhood smoothness term is employed to constrain neighbouring pixels with similar appearances to generate a smooth depth surface. This approach can make the depth of the projected point cloud closer to the real surgical site and preserve realistic details. The authors demonstrate the performance of the method by training and evaluation with a partial nephrectomy da Vinci surgery dataset and heart phantom data from the Hamlyn Centre.After nearly being hunted to extinction during the fur trade of the late 20th Century, sea otter (Enhydra lutris) populations have recovered to varying degrees of their historical range. While overall population numbers and range have increased, there are regions in which expansion has occurred at a slower rate and/or animal numbers have decreased, which may be a result of chronic stress from a variety of sources. Some have employed glucocorticoid analysis in their attempts to validate these explanations. Our goal was to conduct a controlled study using sea otters managed under human care to validate the use of serum glucocorticoid analysis to monitor stress physiology in the sea otter. We used a standard ACTH challenge test to compare cortisol and corticosterone responses, thereby identifying the primary glucocorticoid in the sea otter. Fourteen sea otters of both sexes (five males, nine females), including juveniles, sub-adults and adults, participated in the study. The results of the testing supported cortisol as the primary glucocorticoid in the sea otter. Sex and age did not affect how the individual responded to the ACTH or saline injection. Interestingly, the saline injection not only confirmed the effects of the ACTH on glucocorticoid release from the adrenal glands but also provided information on how long it takes the sea otter's glucocorticoid levels to return to baseline after capture and sedation. The insight gained from this study will aid in future efforts to better understand the role of stress in free-ranging sea otter populations. Recognition of the primary glucocorticoid will facilitate evaluation of more stable biological material, such as fur or whiskers, which tend to be less affected by the diurnal cycling of glucocorticoids. iFSP1 nmr © The Author(s) 2020. Published by Oxford University Press and the Society for Experimental Biology.