scholarly journals GPU-Based Simulation of Ultrasound Imaging Artifacts for Cryosurgery Training

2016 ◽  
Vol 16 (1) ◽  
pp. 5-14 ◽  
Author(s):  
Robert Keelan ◽  
Kenji Shimada ◽  
Yoed Rabin
Keyword(s):  
Temperature Field ◽  
Ultrasound Imaging ◽  
Ultrasound Image ◽  
Application Programming Interface ◽  
Computational Technique ◽  
Processing Unit ◽  
Computerized Training ◽  
Application Programming ◽  
Imaging Artifacts ◽  
Property Changes

This study presents an efficient computational technique for the simulation of ultrasound imaging artifacts associated with cryosurgery based on nonlinear ray tracing. This study is part of an ongoing effort to develop computerized training tools for cryosurgery, with prostate cryosurgery as a development model. The capability of performing virtual cryosurgical procedures on a variety of test cases is essential for effective surgical training. Simulated ultrasound imaging artifacts include reverberation and reflection of the cryoprobes in the unfrozen tissue, reflections caused by the freezing front, shadowing caused by the frozen region, and tissue property changes in repeated freeze–thaw cycles procedures. The simulated artifacts appear to preserve the key features observed in a clinical setting. This study displays an example of how training may benefit from toggling between the undisturbed ultrasound image, the simulated temperature field, the simulated imaging artifacts, and an augmented hybrid presentation of the temperature field superimposed on the ultrasound image. The proposed method is demonstrated on a graphic processing unit at 100 frames per second, on a mid-range personal workstation, at two orders of magnitude faster than a typical cryoprocedure. This performance is based on computation with C++ accelerated massive parallelism and its interoperability with the DirectX-rendering application programming interface.

scholarly journals LTTng CLUST: A System-Wide Unified CPU and GPU Tracing Tool for OpenCL Applications

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
David Couturier ◽  
Michel R. Dagenais
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Battery Life ◽  
Portable Devices ◽  
Processing Unit ◽  
Central Processing ◽  
Application Programming ◽  
Graphical Processing ◽  
Performance Analysis Tools ◽  
Programming Interface

As computation schemes evolve and many new tools become available to programmers to enhance the performance of their applications, many programmers started to look towards highly parallel platforms such as Graphical Processing Unit (GPU). Offloading computations that can take advantage of the architecture of the GPU is a technique that has proven fruitful in recent years. This technology enhances the speed and responsiveness of applications. Also, as a side effect, it reduces the power requirements for those applications and therefore extends portable devices battery life and helps computing clusters to run more power efficiently. Many performance analysis tools such as LTTng, strace and SystemTap already allow Central Processing Unit (CPU) tracing and help programmers to use CPU resources more efficiently. On the GPU side, different tools such as Nvidia’s Nsight, AMD’s CodeXL, and third party TAU and VampirTrace allow tracing Application Programming Interface (API) calls and OpenCL kernel execution. These tools are useful but are completely separate, and none of them allow a unified CPU-GPU tracing experience. We propose an extension to the existing scalable and highly efficient LTTng tracing platform to allow unified tracing of GPU along with CPU’s full tracing capabilities.

scholarly journals Verification of Balloon Integrity by Ultrasound Imaging in Accelerated Partial Breast Irradiation

2016 ◽  
Vol 5 (2) ◽  
pp. 60
Author(s):  
James D Christensen ◽  
Mark G Trombetta ◽  
Olivier Gayou
Keyword(s):  
Ultrasound Imaging ◽  
Measurement Errors ◽  
Ultrasound Image ◽  
Accelerated Partial Breast Irradiation ◽  
Ultrasound Measurement ◽  
Partial Breast Irradiation ◽  
Balloon Size ◽  
False Image ◽  
Imaging Artifacts ◽  
Probe Orientation

<p class="cco-body"><em><span lang="EN-GB">Purpose</span></em><span lang="EN-GB">: An overview of the ultrasound imaging artifacts encountered in Mammosite balloon APBI is presented. Analysis of ultrasound measurement errors and the dosimetric impact of balloon leakage were used to determine whether clinically relevant changes in balloon size can be reliably detected. <em>Methods</em>: Ultrasound imaging of a Mammosite balloon phantom was performed to better understand measurement errors and accuracy. The dose to the prescription point as a function of balloon diameter was computed for different sized balloons. The results were compared to phantom measurements of balloon diameter versus filling volume to assess the dose change that would result from tissue moving inward with a shrinking balloon boundary. In APBI patients undergoing a course of 10 treatment fractions, the accuracy and variability of balloon size measured with ultrasound imaging was compared to CT. <em>Results</em>: Ultrasound artifacts combine to form a false image of the distal balloon boundary. Proper US probe orientation and choice of measurement point locations improved distance measurement accuracy. A 1 mm change in balloon diameter is measurable with ±0.1 mm error and corresponds to &lt;4% change in dose 1 cm from the balloon. Measurement errors relative to CT averaged less than 1.4 mm and variability (standard deviation) over the course of treatment averaged 1.9 mm. <em>Conclusions</em>: Properly performed ultrasound image acquisition and analysis can detect dosimetrically relevant changes in the size of a leaking balloon. This study confirms that US imaging is a valid method of verifying APBI balloon integrity over the course of treatment.</span></p>

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

2018 ◽  
Vol 9 (1) ◽  
pp. 24-31
Author(s):  
Rudianto Rudianto ◽  
Eko Budi Setiawan
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Image Content ◽  
Image File ◽  
Application Programming ◽  
Index Terms ◽  
Programming Interface

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

Is JUUL marketing to kids on social media? Analysis of JUUL Twitter Followers� Age (Preprint)

2018 ◽  
Author(s):  
Annice Kim ◽  
Robert Chew ◽  
Michael Wenger ◽  
Margaret Cress ◽  
Thomas Bukowski ◽  
...  
Keyword(s):  
Social Media ◽  
Application Programming Interface ◽  
Media Analysis ◽  
Prediction Algorithm ◽  
Social Media Networks ◽  
Verification Methods ◽  
Twitter Account ◽  
Application Programming ◽  
Age Verification ◽  
Age Category

BACKGROUND JUUL is an electronic nicotine delivery system (ENDS) resembling a USB device that has become rapidly popular among youth. Recent studies suggest that social media may be contributing to its popularity. JUUL company claims their products are targeted for adult current smokers but recent surveillance suggests youth may be exposed to JUUL products online. To date, there has been little attention on restricting youth exposure to age restricted products on social media. OBJECTIVE The objective of this study was to utilize a computational age prediction algorithm to determine the extent to which underage youth are being exposed to JUUL’s marketing practices on Twitter. METHODS We examined all of @JUULvapor’s Twitter followers in April 2018. For followers with a public account, we obtained their metadata and last 200 tweets using the Twitter application programming interface. We ran a series of classification models to predict whether the account following @JUULvapor was an underage youth or an adult. RESULTS Out of 9,077 individuals following @JUULvapor Twitter account, a three-age category model predicted that 44.9% are 13 to 17 years old (N=4,078), 43.6% are 18 to 24 years old (N=3,957), and 11.5% are 25 years old or older (N=1,042); and a two-age category model predicted that 80.6% (N=7,313) are under 21 years old. CONCLUSIONS Despite a disclaimer that followers must be of legal age to purchase tobacco products, the majority of JUUL followers on Twitter are under age. This suggests that ENDS brands and social media networks need to implement more stringent age-verification methods to protect youth from age-restricted content.

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