The organizational implications of medical imaging in the context of Malaysian hospitals

This research investigated the implementation and use of medical imaging in the context of Malaysian hospitals. In this report medical imaging refers to PACS, RIS/HIS and imaging modalities which are linked through a computer network. The study examined how the internal context of a hospital and its external context together influenced the implementation of medical imaging, and how this in turn shaped organizational roles and relationships within the hospital itself. It further investigated how the implementation of the technology in one hospital affected its implementation in another hospital. The research used systems theory as the theoretical framework for the study. Methodologically, the study used a case-based approach and multiple methods to obtain data. The case studies included two hospital-based radiology departments in Malaysia. The outcomes of the research suggest that the implementation of medical imaging in community hospitals is shaped by the external context particularly the role played by the Ministry of Health. Furthermore, influences from both the internal and external contexts have a substantial impact on the process of implementing medical imaging and the extent of the benefits that the organization can gain. In the context of roles and social relationships, the findings revealed that the routine use of medical imaging has substantially affected radiographers’ roles, and the social relationships between non clinical personnel and clinicians. This study found no change in the relationship between radiographers and radiologists. Finally, the approaches to implementation taken in the hospitals studied were found to influence those taken by other hospitals. Overall, this study makes three important contributions. Firstly, it extends Barley’s (1986, 1990) research by explicitly demonstrating that the organization’s internal and external contexts together shape the implementation and use of technology, that the processes of implementing and using technology impact upon roles, relationships and networks and that a role-based approach alone is inadequate to examine the outcomes of deploying an advanced technology. Secondly, this study contends that scalability of technology in the context of developing countries is not necessarily linear. Finally, this study offers practical contributions that can benefit healthcare organizations in Malaysia

Focal Spot, Winter 2005/2006

https://digitalcommons.wustl.edu/focal_spot_archives/1101/thumbnail.jp

Computer‐assisted learning as an alternative to didactic lectures: A study of teaching the physics of diagnostic imaging

A computer‐assisted learning (CAL) package entitled Physics of Diagnostic Imaging was developed in 1995 to replace five hours of didactic lectures at the University of Glasgow Faculty of Veterinary Medicine, and has been available as an additional learning resource for students in the other five UK veterinary schools for over three years. The package was reviewed by peer experts and the reaction of the students to its use gauged by post‐task questionnaire administration, informal discussions and observation. To assess the effect of integration into the curriculum, analyses of fourth‐year degree examination results over a six‐year period were carried out. Analyses of students’ examination results for pre‐ and post‐CAL delivery of the diagnostic imaging course showed that performance in the CAL‐based course was significantly higher than in other subjects. This confirmed that the courseware can be used to replace didactic lectures as part of a rich learning environment supported by other resources. Initial student resistance to lecture replacement with CAL occurred, but has lessened as the use of the package has become established in the curriculum

Focal Spot, Spring 1988

https://digitalcommons.wustl.edu/focal_spot_archives/1048/thumbnail.jp

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level

Diffeomorphic density registration

In this book chapter we study the Riemannian Geometry of the density registration problem: Given two densities (not necessarily probability densities) defined on a smooth finite dimensional manifold find a diffeomorphism which transforms one to the other. This problem is motivated by the medical imaging application of tracking organ motion due to respiration in Thoracic CT imaging where the fundamental physical property of conservation of mass naturally leads to modeling CT attenuation as a density. We will study the intimate link between the Riemannian metrics on the space of diffeomorphisms and those on the space of densities. We finally develop novel computationally efficient algorithms and demonstrate there applicability for registering RCCT thoracic imaging.Comment: 23 pages, 6 Figures, Chapter for a Book on Medical Image Analysi

Towards automated visual flexible endoscope navigation

Background:\ud The design of flexible endoscopes has not changed significantly in the past 50 years. A trend is observed towards a wider application of flexible endoscopes with an increasing role in complex intraluminal therapeutic procedures. The nonintuitive and nonergonomical steering mechanism now forms a barrier in the extension of flexible endoscope applications. Automating the navigation of endoscopes could be a solution for this problem. This paper summarizes the current state of the art in image-based navigation algorithms. The objectives are to find the most promising navigation system(s) to date and to indicate fields for further research.\ud Methods:\ud A systematic literature search was performed using three general search terms in two medical–technological literature databases. Papers were included according to the inclusion criteria. A total of 135 papers were analyzed. Ultimately, 26 were included.\ud Results:\ud Navigation often is based on visual information, which means steering the endoscope using the images that the endoscope produces. Two main techniques are described: lumen centralization and visual odometry. Although the research results are promising, no successful, commercially available automated flexible endoscopy system exists to date.\ud Conclusions:\ud Automated systems that employ conventional flexible endoscopes show the most promising prospects in terms of cost and applicability. To produce such a system, the research focus should lie on finding low-cost mechatronics and technologically robust steering algorithms. Additional functionality and increased efficiency can be obtained through software development. The first priority is to find real-time, robust steering algorithms. These algorithms need to handle bubbles, motion blur, and other image artifacts without disrupting the steering process

Focal Spot, Winter 1986

https://digitalcommons.wustl.edu/focal_spot_archives/1042/thumbnail.jp

Focal Spot, Spring 1987

https://digitalcommons.wustl.edu/focal_spot_archives/1045/thumbnail.jp