Advances in Automated Generation of Convolutional Neural Networks from Synthetic Data in Industrial Environments

The usage of convolutional neural networks has revolutionized data processing and its application in the industry during the last few years. Especially detection in images, a historically hard task to automate is now available on every smart phone. Nonetheless, this technology has not yet spread in the industry of car production, where lots of visual tests and quality checks are still performed manually. Even though the vision capabilities convolutional neural networks can give machines are already respectable, they still need well prepared training data that is costly and time-consuming to produce. This paper describes our effort to test and improve a system to automatically synthesize training images. This existing system renders computer aided design models into scenes and out of that produces realistic images and corresponding labels. Two new models, Single Shot Detector and RetinaNet are retrained under the use of distractors and then tested against each other. The better performing RetinaNet is then tested for performance under training with a variety of datasets from different domains in order to observe the models strength and weakness under domain shifts. These domains are real photographs, rendered models and images of objects cut and pasted into different backgrounds. The results show that the model trained with a mixture of all domains performs best

Implementing Synthetic Aperture Radar Backprojection in Chisel – A Field Report

Chisel is an emerging hardware description language which is especially popular in the RISC-V community. In this report, we evaluate its application in the field of general digital hardware design. A dedicated hardware implementation of a Synthetic Aperture Radar (SAR) processing algorithm is used as an example case for a real-world application. It is targeting a modern high performance FPGA platform. We analyze the difference in code size compared to a VHDL implementation. In contrast to related publications, we classify the code lines into several categories, providing a more detailed view. Overall, the number of lines was reduced by 74% while the amount of boilerplate code was reduced by 83%. Additionally, we report on our experience using Chisel in this practical application. We found the generative concept and the flexibility introduced by modern software paradigms superior to traditional hardware description languages. This increased productivity, especially during timing closure. However, additional programming skills not associated with classic hardware design are required to fully leverage its advantages. We recommend Chisel as a language for all hardware design tasks and expect its popularity to increase in the future

Planning a future randomized clinical trial based on a network of relevant past trials

Background The important role of network meta-analysis of randomized clinical trials in health technology assessment and guideline development is increasingly recognized. This approach has the potential to obtain conclusive results earlier than with new standalone trials or conventional, pairwise meta-analyses. Methods Network meta-analyses can also be used to plan future trials. We introduce a four-step framework that aims to identify the optimal design for a new trial that will update the existing evidence while minimizing the required sample size. The new trial designed within this framework does not need to include all competing interventions and comparisons of interest and can contribute direct and indirect evidence to the updated network meta-analysis. We present the method by virtually planning a new trial to compare biologics in rheumatoid arthritis and a new trial to compare two drugs for relapsing-remitting multiple sclerosis. Results A trial design based on updating the evidence from a network meta-analysis of relevant previous trials may require a considerably smaller sample size to reach the same conclusion compared with a trial designed and analyzed in isolation. Challenges of the approach include the complexity of the methodology and the need for a coherent network meta-analysis of previous trials with little heterogeneity. Conclusions When used judiciously, conditional trial design could significantly reduce the required resources for a new study and prevent experimentation with an unnecessarily large number of participants

Is Internal Rotation Measurement of the Hip Useful for Ruling in Cam or Pincer Morphology in Asymptomatic Males? A Diagnostic Accuracy Study.

BACKGROUND Cam and pincer morphologies are associated with limited internal rotation. However, the routine clinical examination for hip rotation has limited reliability. A more standardized method of measuring hip rotation might increase test-retest and interobserver reliability and might be useful as a screening test to detect different hip morphologies without the need for imaging. We developed an examination chair to standardize the measurement of internal hip rotation, which improved interobserver reliability. However, the diagnostic test accuracy for this test is unknown. QUESTION/PURPOSE Is a standardized method of determining internal hip rotation using an examination chair useful in detecting cam and pincer morphology with MRI as a reference standard? METHODS A diagnostic test accuracy study was conducted in a sample of asymptomatic males. Using an examination chair with a standardized seated position, internal rotation was measured in 1080 men aged 18 to 21 years who had been conscripted for the Swiss army. The chair prevents compensatory movement by stabilizing the pelvis and the thighs with belts. The force to produce the internal rotation was standardized with a pulley system. Previous results showed that the measurements with the examination chair are similar to clinical assessment but with higher interobserver agreement. A random sample of 430 asymptomatic males was invited to undergo hip MRI. Of those, 244 White European males responded to the invitation and had a mean age of 20 ± 0.7 years and a mean internal rotation of the hip of 33° ± 8.5°. Using MRI as the reference standard, 69% (169 of 244) had a normal hip, 24% (59 of 244) a definite cam morphology (Grades 2 and 3), 3% (8 of 244) an increased acetabular depth, and 3% (8 of 244) a combination of both. One experienced radiologist graded cam morphology as follows: 0 = normal, 1 = mild, 2 = moderate, and 3 = severe. Pincer morphology was defined by increased acetabular depth (≤ 3 mm distance between the center of the femoral neck and the line connecting the anterior and posterior acetabular rims). The intraobserver agreement was substantial (weighted κ of 0.65). A receiver operating characteristic (ROC) curve was fitted, and sensitivity, specificity, and likelihood ratios were estimated for different internal rotation cutoffs. RESULTS For cam morphology, the area under the ROC curve was 0.75 (95% CI 0.67 to 0.82). Internal hip rotation of less than 20° yielded a positive likelihood ratio of 9.57 (sensitivity 0.13, specificity 0.99), and a value of 40° or more resulted in a negative likelihood ratio of 0.36 (sensitivity 0.93, specificity 0.20). The area under the curve for detecting the combination of cam and pincer morphologies was 0.87 (95% CI 0.74 to 1.0). A cutoff of 20° yielded a positive likelihood ratio of 9.03 (sensitivity 0.33, specificity 0.96). CONCLUSION This examination chair showed moderate-to-good diagnostic value to rule in hip cam morphology in White European males. However, at the extremes of the 95% confidence intervals, diagnostic performance would be poor. Nonetheless, we believe this test can contribute to identifying cam morphologies, and we hope that future, larger studies-ideally in more diverse patient populations-will seek to validate this to arrive at more precise estimates of the diagnostic performance of this test. LEVEL OF EVIDENCE Level III, diagnostic study

Cardiovascular safety of non-steroidal anti-inflammatory drugs: network meta-analysis

Objective To analyse the available evidence on cardiovascular safety of non-steroidal anti-inflammatory drugs

Small study effects in meta-analyses of osteoarthritis trials: meta-epidemiological study

Objective To examine the presence and extent of small study effects in clinical osteoarthritis research

A Versatile, Voltage-Pulse Based Read and Programming Circuit for Multi-Level RRAM Cells

In this work, we present an integrated read and programming circuit for Resistive Random Access Memory (RRAM) cells. Since there are a lot of different RRAM technologies in research and the process variations of this new memory technology often spread over a wide range of electrical properties, the proposed circuit focuses on versatility in order to be adaptable to different cell properties. The circuit is suitable for both read and programming operations based on voltage pulses of flexible length and height. The implemented read method is based on evaluating the voltage drop over a measurement resistor and can distinguish up to eight different states, which are coded in binary, thereby realizing a digitization of the analog memory value. The circuit was fabricated in the 130 nm CMOS process line of IHP. The simulations were done using a physics-based, multi-level RRAM model. The measurement results prove the functionality of the read circuit and the programming system and demonstrate that the read system can distinguish up to eight different states with an overall resistance ratio of 7.9

Computational Modeling in Liver Surgery

The need for extended liver resection is increasing due to the growing incidence of liver tumors in aging societies. Individualized surgical planning is the key for identifying the optimal resection strategy and to minimize the risk of postoperative liver failure and tumor recurrence. Current computational tools provide virtual planning of liver resection by taking into account the spatial relationship between the tumor and the hepatic vascular trees, as well as the size of the future liver remnant. However, size and function of the liver are not necessarily equivalent. Hence, determining the future liver volume might misestimate the future liver function, especially in cases of hepatic comorbidities such as hepatic steatosis. A systems medicine approach could be applied, including biological, medical, and surgical aspects, by integrating all available anatomical and functional information of the individual patient. Such an approach holds promise for better prediction of postoperative liver function and hence improved risk assessment. This review provides an overview of mathematical models related to the liver and its function and explores their potential relevance for computational liver surgery. We first summarize key facts of hepatic anatomy, physiology, and pathology relevant for hepatic surgery, followed by a description of the computational tools currently used in liver surgical planning. Then we present selected state-of-the-art computational liver models potentially useful to support liver surgery. Finally, we discuss the main challenges that will need to be addressed when developing advanced computational planning tools in the context of liver surgery.Peer Reviewe