Ultrasound in radiology —state of the art

Author(s):  
David O. Cosgrove

The practice of ultrasound in radiology has continued to develop and shows no signs of slowing down. The changes affect the systems themselves, with important technical developments, as well as the ways they are used, and to some extent these are interlinked. The earliest static scanners were so difficult to use that only dedicated personnel could find the time and make the effort required to use them. This led to a small cohort of enthusiasts offering a limited and expensive service. Strangely, they were a mixture of doctors (many of whom were not radiologists) and physicists, perhaps reflecting the complexity of the scanners. with the development of real-time systems and increasingly as they have become easier to operate, ultrasound found its place within radiology departments and, in parallel, in cardiology and obstetric units as well as in vascular labs. Here the role of physicists faded and most of the people performing the scans were medical, a situation that still obtains in many parts of the world, notably in the Far East (in China, the doctors are ultrasound specialists) and in many European countries. In others, especially in the United States, technologists or radiographers took over the actual scanning, leaving radiologists or their equivalent (cardiologists, obstetricians) to read and report the studies by analogy with other scanning modalities such as computed tomography (CT) and magnetic resonance imaging (MRI). The driver for this major change has mainly been financial: medics are expensive and sharing the workload with technologists is cost-effective. However, this shift comes with a penalty: as ultrasound is a real-time method and the techniques required to make the studies are very interactive, simply reading a set of images on a PACS (picture archiving and communication system) workstation deprives the radiologist of dynamic information that can be critical to making the diagnosis. In some places the response to this has been to train the technicians or radiographers to interpret and report their own cases. Though often disapproved of by the regulatory authorities and exposing practitioners to risks of litigation, this approach has been popular amongst radiographers only partly because their extended role is rewarded by additional pay.

Author(s):  
Anjushi Verma ◽  
Ankur Ghartaan ◽  
Tirthankar Gayen

Real time systems are those systems which must guarantee to response correctly within strict time constraint or within deadline. Failures can arise from both functional errors as well as timing bugs. Hence, it is necessary to provide temporal correctness of programs used in real time applications in addition to providing functional correctness. Although, there are several researches concerned with achieving fault tolerance in the presence of various functional and operational errors but many of them did not address the problem concerned with the timing bugs which is an important issue in real time systems. As for real time systems, many times it becomes a necessity for a given service to be delivered within the specified time deadline. Therefore, this paper reviews the existing approaches from the perspective of  real time systems to analyse the shortcomings of these approaches to  present a versatile and cost effective approach in the presence of timing bugs for providing fault tolerance to enhance the reliability of the real time software applications.


Author(s):  
Anjushi Verma ◽  
Ankur Ghartaan ◽  
Tirthankar Gayen

Real time systems are those systems which must guarantee to response correctly within strict time constraint or within deadline. Failures can arise from both functional errors as well as timing bugs. Hence, it is necessary to provide temporal correctness of programs used in real time applications in addition to providing functional correctness. Although, there are several researches concerned with achieving fault tolerance in the presence of various functional and operational errors but many of them did not address the problem concerned with the timing bugs which is an important issue in real time systems. As for real time systems, many times it becomes a necessity for a given service to be delivered within the specified time deadline. Therefore, this paper reviews the existing approaches from the perspective of  real time systems to analyse the shortcomings of these approaches to  present a versatile and cost effective approach in the presence of timing bugs for providing fault tolerance to enhance the reliability of the real time software applications.


2019 ◽  
Author(s):  
Seyyed Ali Davari ◽  
Anthony S. Wexler

Abstract. The United States Environmental Protection Agency (US EPA) list of Hazardous Air Pollutants (HAPs) includes metal elements suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metallic elements in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost effective technique that can be used for analyzing toxic metallic elements in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metallic elements targeted by US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. Least Absolute Shrinkage and Selection Operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metallic elements from the observed spectra. The limits of detections (LOD) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however for some elements the single-feature LOD marginally outperforms LASSO LOD. The combination of low cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data driven solutions to costly measurements.


2020 ◽  
Vol 13 (10) ◽  
pp. 5369-5377
Author(s):  
Seyyed Ali Davari ◽  
Anthony S. Wexler

Abstract. The United States Environmental Protection Agency (US EPA) list of hazardous air pollutants (HAPs) includes toxic metal suspected or associated with development of cancer. Traditional techniques for detecting and quantifying toxic metals in the atmosphere are either not real time, hindering identification of sources, or limited by instrument costs. Spark emission spectroscopy is a promising and cost-effective technique that can be used for analyzing toxic metals in real time. Here, we have developed a cost-effective spark emission spectroscopy system to quantify the concentration of toxic metals targeted by the US EPA. Specifically, Cr, Cu, Ni, and Pb solutions were diluted and deposited on the ground electrode of the spark emission system. The least absolute shrinkage and selection operator (LASSO) was optimized and employed to detect useful features from the spark-generated plasma emissions. The optimized model was able to detect atomic emission lines along with other features to build a regression model that predicts the concentration of toxic metals from the observed spectra. The limits of detections (LODs) were estimated using the detected features and compared to the traditional single-feature approach. LASSO is capable of detecting highly sensitive features in the input spectrum; however, for some toxic metals the single-feature LOD marginally outperforms LASSO LOD. The combination of low-cost instruments with advanced machine learning techniques for data analysis could pave the path forward for data-driven solutions to costly measurements.


2021 ◽  
Author(s):  
Katharine Harrington ◽  
Shannon N Zenk ◽  
Linda Van Horn ◽  
Lauren Giurini ◽  
Nithya Mahakala ◽  
...  

BACKGROUND As poor diet quality is a significant risk factor for multiple noncommunicable diseases prevalent in the United States, it is important that methods be developed to accurately capture eating behavior data. There is growing interest in the use of ecological momentary assessments to collect data on health behaviors and their predictors on a micro timescale (at different points within or across days); however, documenting eating behaviors remains a challenge. OBJECTIVE This pilot study (N=48) aims to examine the feasibility—usability and acceptability—of using smartphone-captured and crowdsource-labeled images to document eating behaviors in real time. METHODS Participants completed the Block Fat/Sugar/Fruit/Vegetable Screener to provide a measure of their typical eating behavior, then took pictures of their meals and snacks and answered brief survey questions for 7 consecutive days using a commercially available smartphone app. Participant acceptability was determined through a questionnaire regarding their experiences administered at the end of the study. The images of meals and snacks were uploaded to Amazon Mechanical Turk (MTurk), a crowdsourcing distributed human intelligence platform, where 2 Workers assigned a count of food categories to the images (fruits, vegetables, salty snacks, and sweet snacks). The agreement among MTurk Workers was assessed, and weekly food counts were calculated and compared with the Screener responses. RESULTS Participants reported little difficulty in uploading photographs and remembered to take photographs most of the time. Crowdsource-labeled images (n=1014) showed moderate agreement between the MTurk Worker responses for vegetables (688/1014, 67.85%) and high agreement for all other food categories (871/1014, 85.89% for fruits; 847/1014, 83.53% for salty snacks, and 833/1014, 81.15% for sweet snacks). There were no significant differences in weekly food consumption between the food images and the Block Screener, suggesting that this approach may measure typical eating behaviors as accurately as traditional methods, with lesser burden on participants. CONCLUSIONS Our approach offers a potentially time-efficient and cost-effective strategy for capturing eating events in real time.


2017 ◽  
Vol 29 (4) ◽  
pp. 522-528 ◽  
Author(s):  
Katherine A. Sayler ◽  
Troy Bigelow ◽  
Leo G. Koster ◽  
Sabrina Swenson ◽  
Courtney Bounds ◽  
...  

Despite successful eradication of pseudorabies virus (PRV) from the commercial pig industry in the United States in 2004, large populations of feral swine in certain regions act as wildlife reservoirs for the virus. Given the threat of reintroduction of the virus into domestic herds, a rapid, reliable, easily implemented assay is needed for detection of PRV. Although a real-time PCR (rtPCR) assay exists, improvements in rtPCR technology and a greater understanding of the diversity of PRV strains worldwide require an assay that would be easier to implement, more cost effective, and more specific. We developed a single-tube, rapid rtPCR that is capable of detecting 10 copies of PRV glycoprotein B ( gB) DNA per 20-µL total volume reaction. The assay did not produce a false-positive in samples known to be negative for the virus. The assay was negative for genetically similar herpesviruses and other porcine viruses. Our assay is a highly specific and sensitive assay that is also highly repeatable and reproducible. The assay should be a useful tool for early detection of PRV in pigs in the case of a suspected introduction or outbreak situation.


10.2196/27512 ◽  
2021 ◽  
Vol 5 (12) ◽  
pp. e27512
Author(s):  
Katharine Harrington ◽  
Shannon N Zenk ◽  
Linda Van Horn ◽  
Lauren Giurini ◽  
Nithya Mahakala ◽  
...  

Background As poor diet quality is a significant risk factor for multiple noncommunicable diseases prevalent in the United States, it is important that methods be developed to accurately capture eating behavior data. There is growing interest in the use of ecological momentary assessments to collect data on health behaviors and their predictors on a micro timescale (at different points within or across days); however, documenting eating behaviors remains a challenge. Objective This pilot study (N=48) aims to examine the feasibility—usability and acceptability—of using smartphone-captured and crowdsource-labeled images to document eating behaviors in real time. Methods Participants completed the Block Fat/Sugar/Fruit/Vegetable Screener to provide a measure of their typical eating behavior, then took pictures of their meals and snacks and answered brief survey questions for 7 consecutive days using a commercially available smartphone app. Participant acceptability was determined through a questionnaire regarding their experiences administered at the end of the study. The images of meals and snacks were uploaded to Amazon Mechanical Turk (MTurk), a crowdsourcing distributed human intelligence platform, where 2 Workers assigned a count of food categories to the images (fruits, vegetables, salty snacks, and sweet snacks). The agreement among MTurk Workers was assessed, and weekly food counts were calculated and compared with the Screener responses. Results Participants reported little difficulty in uploading photographs and remembered to take photographs most of the time. Crowdsource-labeled images (n=1014) showed moderate agreement between the MTurk Worker responses for vegetables (688/1014, 67.85%) and high agreement for all other food categories (871/1014, 85.89% for fruits; 847/1014, 83.53% for salty snacks, and 833/1014, 81.15% for sweet snacks). There were no significant differences in weekly food consumption between the food images and the Block Screener, suggesting that this approach may measure typical eating behaviors as accurately as traditional methods, with lesser burden on participants. Conclusions Our approach offers a potentially time-efficient and cost-effective strategy for capturing eating events in real time.


2005 ◽  
Vol 71 (11) ◽  
pp. 6702-6710 ◽  
Author(s):  
J. A. Tomlinson ◽  
N. Boonham ◽  
K. J. D. Hughes ◽  
R. L. Griffin ◽  
I. Barker

ABSTRACT Phytophthora ramorum is a recently described pathogen causing oak mortality (sudden oak death) in forests in coastal areas of California and southern Oregon and dieback and leaf blight in a range of tree, shrub, and herbaceous species in the United States and Europe. Due to the threat posed by this organism, stringent quarantine regulations are in place, which restrict the movement of a number of hosts. Fast and accurate diagnostic tests are required in order to characterize the distribution of P. ramorum, prevent its introduction into pathogen-free areas, and minimize its spread within affected areas. However, sending samples to a laboratory for testing can cause a substantial delay between sampling and diagnosis. A rapid and simple DNA extraction method was developed for use at the point of sampling and used to extract DNAs from symptomatic foliage and stems in the field. A sensitive and specific single-round real-time PCR (TaqMan) assay for P. ramorum was performed using a portable real-time PCR platform (Cepheid SmartCycler II), and a cost-effective method for stabilizing PCR reagents was developed to allow their storage and transportation at room temperature. To our knowledge, this is the first description of a method for DNA extraction and molecular testing for a plant pathogen carried out entirely in the field, independent of any laboratory facilities.


IEE Review ◽  
1992 ◽  
Vol 38 (3) ◽  
pp. 112
Author(s):  
Stuart Bennett

Sign in / Sign up

Export Citation Format

Share Document