A method for vessel segmentation and tracking in ultrasound images using Kalman filters is presented. A modified Star-Kalman algorithm is used to determine vessel contours and ellipse parameters using an extended Kalman filter with an elliptical model. The parameters can be used to easily calculate the transverse vessel area which is of clinical use. A temporal Kalman filter is used for tracking the vessel center over several frames, using location measurements from a handheld sensorized ultrasound probe. The segmentation and tracking have been implemented in real-time and validated using simulated ultrasound data with known features and real data, for which expert segmentation was performed. Results indicate that mean errors between segmented contours and expert tracings are on the order of 1%-2% of the maximum feature dimension, and that the transverse cross-sectional vessel area as computed from estimated ellipse parameters a, b as determined by our algorithm is within 10% of that determined by experts. The location of the vessel center was tracked accurately for a range of speeds from 1.4 to 11.2 mm/s.

A system for objective vessel compression assessment for deep venous thrombosis characterization using ultrasound image data and a sensorized ultrasound probe is presented. Two new objective measures calculated from applied force and transverse vessel area are also presented and used to describe vessel compressibility. A modified star-Kalman algorithm is used for feature detection in acquired ultrasound images, and objective measures of vessel compressibility are calculated from the detected features and acquired force and location data from the sensorized probe. A three-dimensional shape model of the examined vessel that includes compressibility measures mapped as colors to its surface is presented on the user interface, as well as a virtual representation of the image plane. The compressibility measures were validated using expert segmentation of healthy and diseased vessels and compared using paired t-tests, which showed a significant difference between healthy and diseased cases for both measures. 100% sensitivity and specificity were obtained for both measures. The system was implemented in real-time (16 Hz) and evaluated using a tissue phantom and on healthy human subjects. Sensitivity was 100% and 60%, while specificity was 97% for both measures when implemented. The initial results for the system and its components are promising.

No abstract

ABSTRACT:Underground pipelines pose numerous challenges to 3D visualization. Pipes and cables are conceptually simple and narrow objects with clearly defined shapes, spanned over large geographical areas and made of multiple segments. Pipes are usually maintained as linear objects in the databases. However, the visualization of lines in 3D is difficult to perceive as such lines lack the volumetric appearance, which introduces depth perception and allows understanding the disposition and relationships between the objects on the screen. Therefore the lines should be replaced by volumetric shapes, such as parametric shapes (cylinders) or triangular meshes. The reconstruction of the 3D shape of the pipes has to be done on the fly and therefore it is important to select a 3D representation which will not degrade the performance. If a reconstruction method provides a good performance, the visualization of pipes and cables is guaranteed to provide a smooth experience to the final user, enabling richer scenes but also establishing the visualization requirements in terms of hardware and software to display underground utilities.This paper presents our investigations on a strategy for creating a 3D pipes for 3D visualisation. It is assumed that the pipelines are stored in a database and portions of them are retrieved for 3D reconstruction and 3D visualization. Generally, the reconstruction of underground utilities can be performed in different ways and should lead to realistic appearance, produce visual continuity between segments, include objects depicting specific connections and even consider buffer volumes displaying the uncertainty and the security distance between objects. The creation of such visually pleasing reconstructions may require very detailed shapes, which will increase the complexity of the scene and degrade the performance. This research has identified four criteria to measure the complexity of the scene and conclude on a 3D reconstruction strategy: number of scene graph nodes, number of triangles and vertices on the screen, needed transformations and appearance options. On the basis of these criteria a testing framework is developed. Ten different strategies for 3D reconstruction are defined and tested for X3D, X3DOM and WebGL. The paper analyses the results of the tests and concludes on the best strategy.

Novel energy and atom efficiency processes will be keys to develop the sustainable chemical industry of the future. Electrification could play an important role, by allowing to fine-tune energy input...

We developed a simple and versatile approach for the electrochemical growth of hybrid ZnO|molecular catalyst nanostructured layers. Metal oxide|catalyst hybrid nanoporous layers with a sponge-like structure at the nanoscale and multiscale three-dimensional (3D) hierarchical structures based on nanoporous zinc oxide (ZnO) layers grown on ZnO nanorods were obtained. The thickness and structure of the hybrid nanoporous layers as well as the catalyst concentration can be tuned. This method allows the introduction of water-soluble molecular catalysts based on porphyrin and/or phthalocyanine derivatives into the ZnO matrix with a homogeneous distribution of the complex into the material. As an illustrative example, combining hybrid ZnO with a very low concentration of an encapsulated Co-based molecular catalyst inside the oxide layer results in a 97% catalytic response toward CO 2 reduction to CO with large currents in an organic solvent, highlighting the excellent electrocatalytic activities of such layers, which combine porosity, electronic conductivity, and synergetic properties from its components.

Segmenting vegetation in color images is a complex task, especially when the background and lighting conditions of the environment are uncontrolled. This paper proposes a vegetation segmentation algorithm that combines a supervised and an unsupervised learning method to segment healthy and diseased plant images from the background. During the training stage, a Self-Organizing Map (SOM) neural network is applied to create different color groups from a set of images containing vegetation, acquired from a tomato greenhouse. The color groups are labeled as vegetation and non-vegetation and then used to create two color histogram models corresponding to vegetation and non-vegetation. In the online mode, input images are segmented by a Bayesian classifier using the two histogram models. This algorithm has provided a qualitatively better segmentation rate of images containing plants’ foliage in uncontrolled environments than the segmentation rate obtained by a color index technique, resulting in the elimination of the background and the preservation of important color information. This segmentation method will be applied in disease diagnosis of tomato plants in greenhouses as future work

Study question What is the effect of mRNA SARS-CoV-2 vaccines on oocyte donors regarding oocyte quality, embryo development and clinical outcomes? Summary answer Oocyte quality, fertilization, blastocyst formation, embryo quality and pregnancy rates were similar following donors' mRNA SARS-CoV-2 vaccination compared to previous oocyte donation cycles. What is known already The severe acute respiratory syndrome Coronavirus 2 (SARS–CoV-2) infection, urged scientists to develop safe and effective vaccines. During the ongoing pandemic, the scientific community has promoted vaccination programs to reduce morbidity and mortality. While it has been suggested that SARS–CoV-2 infection might impact fertility, limited evidence shows that vaccination has no influence on sperm parameters, follicular steroidogenesis, or oocyte quality and only one study reported no effects on fertilization or top-quality embryos rate in vaccinated patients undergoing IVF. There is a paucity of evidence with regards to younger population undergoing ovarian stimulation. Study design, size, duration This prospective, multicentre cohort study evaluated 32 oocyte donors with two controlled and similar ovarian stimulation, before and after complete SARS-CoV-2 vaccination, between November 2020 and January 2022. A total of 64 oocyte recipient cycles were analysed equally separately into these two groups. Severe male factor was excluded. Participants/materials, setting, methods Complete SARS-CoV-2 vaccination of the oocyte donor made the difference between the two groups of recipients analysed. The time frame between the previous ovarian stimulation and the vaccination was lower than 8 months. We evaluated and compared the rates of matured eggs (metaphase II, MII), the fertilization and blastocyst formation rates, blastocyst quality (A/B ASEBIR categories), positive pregnancy test and clinical pregnancy rates in both groups of recipients. The statistical analysis was performed using SPSS. Main results and the role of chance The average number of MII collected were similar before and following vaccination (12.23 vs 12.91, p = 0.198, respectively). In recipients, the outcomes with regards to fertilization rate (81.4% vs 77.3% p = 0.210), blastocyst formation rate (60.2% vs 61.5%, p = 0.771) and high-quality blastocysts (quality A: 31.1% vs 36.4% and quality B: 29.0% vs 25.1%, p = 0.430) did not differ statistically between the control group (n = 32, pre-vaccination) and the study group (n = 32, post-vaccination), respectively. Furthermore, regarding clinical outcomes, there were not statistically differences in pregnancy rates (64.0% vs 77.4%, p = 0.269) or clinical pregnancy rates (60.0% vs 64.5%, p = 0.729) before and after vaccination respectively. Limitations, reasons for caution Our encouraging results should be interpreted with caution due to the small sample size and the short period of follow-up. Larger controlled trials are needed to corroborate our findings as the countries continue making forward with the vaccination campaign. Wider implications of the findings The present study suggests no influence of mRNA SARS-CoV2 vaccines on donor oocyte cycles, reflecting no detrimental effects on the assisted reproduction outcomes. The safety of SARS-CoV-2 vaccination concerning IVF cycles is encouraging for the medical community and the health of our patients. Trial registration number Not Applicable