27 research outputs found
joshy/meta: Meta - Make a PACS searchable
No full text<p>Starting with version v2.3.1 to have it citable via zenodo.</p>
PACS-RIS Crawler v1.0.2
No full textA unified search application to link PACS exams with the RIS reports
Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium
No full textBackground: Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accuracy or reliability. Rather than deploying a fully automatic black-box, we propose to incorporate the automated LA volumetry into a human-centric interactive image-analysis process.
Methods and results: Atri-U, an automated data analysis pipeline for long-axis cardiac cine images, computes the atrial volume by: (i) detecting the end-systolic frame, (ii) outlining the endocardial borders of the LA, (iii) localizing the mitral annular hinge points and constructing the longitudinal atrial diameters, equivalent to the usual workup done by clinicians. In every step human interaction is possible, such that the results provided by the algorithm can be accepted, corrected, or re-done from scratch. Atri-U was trained and evaluated retrospectively on a sample of 300 patients and then applied to a consecutive clinical sample of 150 patients with various heart conditions. The agreement of the indexed LA volume between Atri-U and two experts was similar to the inter-rater agreement between clinicians (average overestimation of 0.8 mL/m2 with upper and lower limits of agreement of - 7.5 and 5.8 mL/m2, respectively). An expert cardiologist blinded to the origin of the annotations rated the outputs produced by Atri-U as acceptable in 97% of cases for step (i), 94% for step (ii) and 95% for step (iii), which was slightly lower than the acceptance rate of the outputs produced by a human expert radiologist in the same cases (92%, 100% and 100%, respectively). The assistance of Atri-U lead to an expected reduction in reading time of 66%-from 105 to 34 s, in our in-house clinical setting.
Conclusions: Our proposal enables automated calculation of the maximum LA volume approaching human accuracy and precision. The optional user interaction is possible at each processing step. As such, the assisted process sped up the routine CMR workflow by providing accurate, precise, and validated measurement results
Pulmonary transit time of cardiovascular magnetic resonance perfusion scans for quantification of cardiopulmonary haemodynamics
No full textDevelopment and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning
No full textPurpose: During the emerging COVID-19 pandemic, radiology departments faced a substantial increase in chest
CT admissions coupled with the novel demand for quantification of pulmonary opacities. This article describes
how our clinic implemented an automated software solution for this purpose into an established software
platform in 10 days. The underlying hypothesis was that modern academic centers in radiology are capable of
developing and implementing such tools by their own efforts and fast enough to meet the rapidly increasing
clinical needs in the wake of a pandemic.
Method: Deep convolutional neural network algorithms for lung segmentation and opacity quantification on
chest CTs were trained using semi-automatically and manually created ground-truth (Ntotal = 172). The performance of the in-house method was compared to an externally developed algorithm on a separate test subset
(N = 66).
Results: The final algorithm was available at day 10 and achieved human-like performance (Dice coefficient = 0.97). For opacity quantification, a slight underestimation was seen both for the in-house (1.8 %) and for
the external algorithm (0.9 %). In contrast to the external reference, the underestimation for the in-house algorithm showed no dependency on total opacity load, making it more suitable for follow-up.
Conclusions: The combination of machine learning and a clinically embedded software development platform
enabled time-efficient development, instant deployment, and rapid adoption in clinical routine. The algorithm
for fully automated lung segmentation and opacity quantification that we developed in the midst of the COVID19 pandemic was ready for clinical use within just 10 days and achieved human-level performance even in
complex cases
Analysis of stress and stress management interventions among employees in the information technology (IT) sector in India and Ireland
No full textThe health of people in the work place -in all sectors- has been an important issue for
sometime, and there is substantial evidence that the workplace can have an impact upon
employee health – both positive and negative. As a result, the management of employee
well-being has become a priority for all types of organizations. (Arnold et al, 2010 p 433)
The degree of competition in the economy has becomes more intense as a result of the recent
recession, therefore no job is stress free. Everyone in the workplace experiences some kind of
stress be it in relation to the job or in relation to the general work environment. (Swaminathan
and Rajkumar 2013)
Information Technology has created a positive impact on the lives of millions across the
globe. Today a country’s IT potential is paramount in its march towards global
competitiveness, and is a huge driver of growth. (IBEF, no date)
Stress is an inevitable factor in the life of an employee in the IT sector. It affects the
performance of an employee and detracts the ability of the employee to contribute to the
organization. The effects of stress at work are an important area of concern among the top
management of many business organizations today.
This study analyzes the causes of stress and its impact on absenteeism among IT employees
in Ireland and India. It also examines various coping strategies adopted by IT employees in
Ireland and India. The study also analyzes the impact of stress management intervention on
stress among employees of IT companies in both countries. The study was conducted among
109 employees working in the IT sector in India and Ireland using survey in the form of self
administered questionnaires and found a) factors intrinsic to the job b) organizational
structure and climate and c) role of the employee in the organization as the major causes of
stress among the IT employees in both countries. The study also found that more of the
respondents did not have any access to stress management interventions, and that stress did
not have any significant impact on absenteeism. Author keywords: Stress, occupational stress, absenteeism, coping strategies, work-life balance, productivity, stress management intervention
Artificial Intelligence in Musculoskeletal Imaging: Review of Current Literature, Challenges, and Trends
No full textArtificial intelligence (AI) has gained major attention with a rapid increase in the number of published articles, mostly recently. This review provides a general understanding of how AI can or will be useful to the musculoskeletal radiologist. After a brief technical background on AI, machine learning, and deep learning, we illustrate, through examples from the musculoskeletal literature, potential AI applications in the various steps of the radiologist's workflow, from managing the request to communication of results. The implementation of AI solutions does not go without challenges and limitations. These are also discussed, as well as the trends and perspectives.LTS
Website Analysis for Parental Control
No full textAbstractMan today is in the digital prison-house of infotainment from where he can never be bailed out. The Internet has become the first and the best choice for users all over the world for information as well as knowledge. Information present in the websites is crucial in shaping public awareness and determining the extent of satisfaction of the user. The expose of the online content is through the amazing invention of the websites. Even children and teenagers spend most of their time surfing unrestrictedly site after site, some of these sites capable of highly detrimental impact on their mental and physical health, apart from leading them to devastating juvenile delinquencies. Parents are not always aware of these dangerous cyber-adventures their children dare. This work, in an attempt to find effective technological checks to this growing cyber malady of far reaching consequences to the young world, probes various possibilities of analyzing the websites in many respects, thereby enhancing parental skills to keep watch on their childrens day-to-day internet wanderings in order to lead them away from the temptingly dressed perilous pits to which the internet often beckons the young. The operational scope of the work can be extended to all fields where the user roams around online
