Integration of medical images into the total hospital information system-experiences at Kochi Medical School

Kurihara, Yukio; Okuhara, Yoshiyasu; Narita, Yuichi; Kitazoe, Yasuhiro; Sawada, Akihiro; Shoji, Yasuhiro

doi:10.1109/hicss.1999.773020

Cited by 5 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, the system may not be user friendly or cannot readily be integrated with existing work practices or with other systems. For example, research evidence concerning the organizational and contextual issues related to the integration of new technologies into hospital information systems has been published (Anderson, 1997;Kurihara et al, 1999;Pouloudi, 1999). The successful integration of new technologies with existing systems in a particular hospital context relies on the successful collaboration of developers, users, and the organizations where they work.…”

Section: Ethical Issues As Stakeholder Issuesmentioning

confidence: 98%

Neural Expert Systems in Medical Image Interpretation: Development, Use, and Ethical Issues

Pouloudi¹,

Magoulas²

2000

Journal of Intelligent Systems

View full text Add to dashboard Cite

In this paper, the appropriate level and role of neural network-based methodologies in the development and use of expert systems for medical image interpretation is investigated as technical, organizational, and social issues become intertwined. The notion of the information life cycle is applied to highlight ethical issues during the acquisition, processing and storage, dissemination and use of clinical information. These issues are further analyzed from a stakeholder perspective to accentuate the role of human agents in avoiding ethical risks. Relevant stakeholders, other than the key participants-namely system developers and medical users-are identified. The results of this analysis indicate that each stage of the development and use of a neural expert system entails ethical issues. Significantly, the responsibility for medical image interpretation is affected by contextual factors and should be shared amongst the main stakeholders. These conclusions are useful for the stakeholder groups that are conscious of their obligation to behave ethically and for researchers who wish to investigate further the ethical implications of artificial intelligence use in medicine. +

show abstract

Section: Ethical Issues As Stakeholder Issuesmentioning

confidence: 98%

Neural Expert Systems in Medical Image Interpretation: Development, Use, and Ethical Issues

Pouloudi¹,

Magoulas²

2000

Journal of Intelligent Systems

View full text Add to dashboard Cite

show abstract

“…Next, the image is scaled by normalizing its size. This step requires obtaining the image size ratio parameter from the image file header, stored using the digital imaging and communication in medicine 3 standard in the picture archiving and communication system 4 used in the Hospital Information System 5 of medical institutions. The image is scaled using the parameter to restore it to its original size before application of any zooming during acquisition and storage.…”

Section: Image Preprocessingmentioning

confidence: 99%

A Computer-aided Multidisease Diagnostic System Using MRCP

Logeswaran

2007

J Digit Imaging

View full text Add to dashboard Cite

Automated computer analysis of magnetic resonance cholangiopancreatography (MRCP) (a focused magnetic resonance imaging sequence for the pancreatobiliary region of the abdomen) images for biliary diseases is a difficult problem because of the large inter- and intrapatient variations in the images, varying acquisition settings, and characteristics of the images, defeating most attempts to produce computer-aided diagnosis systems. This paper proposes a system capable of automated preliminary diagnosis of several diseases affecting the bile ducts in the liver, namely, dilation, stones, tumor, and cyst. The system first identifies the biliary ductal structure present in the MRCP images, and then proceeds to determine the presence or absence of the diseases. Tested on a database of 593 clinical images, the system, which uses visual-based features, has shown to be successful in delivering good performance of 70-90% even in the presence of multiple diseases, and may be useful in aiding medical practitioners in routine MRCP examinations.

show abstract

“…Setting up a new department offers the ideal window to allow the transition to a 'filmless' hospital. [14][15][16] Orthopaedic imaging is entering the new millennium with a solid record of recent advances in digital, cross-sectional, and interventional radiology. Advances in radiology have been invaluable in orthopaedics and trauma surgery, but careful thought will be needed to solve the many problems which will arise in the future.…”

Section: Digital Image Output and Image Accessmentioning

confidence: 99%