Computer-aided detection (CAD) tool design for chest pattern recognition training of radiographers

Abstract : The technological advances in radiography, along with the increasing role played by radiographers, require a shift in the training of radiographers at undergraduate level. One of the major shifts has been in the use of technology for learning, teaching and assessment (LTA) which plays an important role in the development of both explicit and implicit knowledge. There has thus been increased interest in the use of technology-enhanced learning, teaching and assessment (TELTA) in radiography education. One of the approaches to the use of TELTA has been the implementation of various virtual tools, including computer-aided detection (CAD) tools. The aim of this exploratory design science research (DSR) study was to design a CAD tool for training student radiographers in chest pattern recognition, followed by the evaluation thereof and exploration of the students experience of the CAD tool. The study employed the DSR methodology which was implemented in five phases: a) awareness of the problem, b) suggestion, c) development, d) evaluation and e) conclusion. The CAD tool (artefact) was designed using Microsoft Visual Studio which operates on the Structured Query Language (SQL) server. The artefact was then evaluated using a combination of quantitative and qualitative approaches. The designed artefact could not be tested for usability with the students as originally intended because of a few technical challenges. The System Usability Scale (SUS) was used to quantitatively evaluate the artefact and revealed that the artefact had an average score of 70.1, exceeding the score of 68 which is generally accepted to indicate that the artefact has good usability. The qualitative evaluation revealed that the artefact was designed adequately while identifying the limitations that prevented the version of the software to be implemented for wider usage. The study only addressed two out of the four objectives that were originally planned for the study. The objectives that were realised were the actual design of the artefact and the evaluation of its usability including its ability to allow timeous communication (and feedback) between the instructor and the students. The two objectives that were planned for exploring how the students experience the artefact and if it enhances their implicit skills, were not realised. In retrospect, the original study plan was over ambitious to have set four objectives to be achieved within a limited period of time.D.Tech. (Radiography

Patient-specific modelling in orthopedics: from image to surgery

In orthopedic surgery, to decide upon intervention and how it can be optimized, surgeons usually rely on subjective analysis of medical images of the patient, obtained from computed tomography, magnetic resonance imaging, ultrasound or other techniques. Recent advancements in computational performance, image analysis and in silico modeling techniques have started to revolutionize clinical practice through the development of quantitative tools, including patient#specific models aiming at improving clinical diagnosis and surgical treatment. Anatomical and surgical landmarks as well as features extraction can be automated allowing for the creation of general or patient-specific models based on statistical shape models. Preoperative virtual planning and rapid prototyping tools allow the implementation of customized surgical solutions in real clinical environments. In the present chapter we discuss the applications of some of these techniques in orthopedics and present new computer-aided tools that can take us from image analysis to customized surgical treatment

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 292)

This bibliography lists 192 reports, articles and other documents introduced into the NASA scientific and technical information system in December, 1986

Numerical Simulation and Design of COVID-19 Disease Detection System Based on Improved Computing Techniques

The high demand for testing the sickness has led to a lack of resources at emergency clinics as the coronavirus epidemic continues. PC vision-based frameworks can be used to increase the productivity of Coronavirus localization. However, a significant amount of information preparation is needed to create an accurate and reliable model, which is currently impractical given the peculiar nature of the illness. One such model is for differentiating pneumonia cases by using radiographs, and it has achieved sufficiently high exactness to be used on patients. Various models are currently being used inside the medical services sector to order different illnesses. This proposal evaluates the benefit of using motion learning to broaden the presentation of the Coronavirus location model, starting from the premise that there is limited information available for Coronavirus ID. Infections that affect the human lungs include viral pneumonia caused by the coronavirus and other viruses. The World Health Organization (W.H.O.) proclaimed Covid a pandemic in 2020; the sickness originated in China and quickly spread to other countries. Early diagnosis of infected patients aids in saving the patient's life and prevents the infection's further spread. As one of the quickest and least expensive methods for diagnosing the condition, the convolutional neural organization (CNN) model is suggested in this research study to assist in the early detection of the infection using chest X-Beam images. Two convolutional brain organizations (CNN) models were created using two different datasets. The primary model was created for double characterization using one of the datasets that only included pneumonia cases and common chest X-Beam images. The second model made use of the information advanced by the primary model using move learning and was created for three class divisions on chest X-Beam images of cases with the coronavirus, pneumonia, and regular cases

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 291)

This bibliography lists 131 reports, articles and other documents introduced into the NASA scientific and technical information system in November 1986

Health Sciences undergraduate handbook

2003 undergraduate handbook for the faculty of Health Science

Focal Spot, Summer 1993

https://digitalcommons.wustl.edu/focal_spot_archives/1064/thumbnail.jp

Focal Spot, Spring 1993

https://digitalcommons.wustl.edu/focal_spot_archives/1063/thumbnail.jp

Fiscal year 1973 scientific and technical reports, articles, papers, and presentations

Formal NASA technical reports, papers published in technical journals, and presentations by MSFC personnel in FY73 are presented. Papers of MSFC contractors are also included