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Facilitating multi-disciplinary, knowledge-based support for breast cancer screening

Facilitating multi-disciplinary, knowledge-based support for breast cancer screening
Facilitating multi-disciplinary, knowledge-based support for breast cancer screening
In order to increase the accuracy of breast cancer screening, the diagnostics of imaging modalities (X-ray, ultrasound or magnetic resonance (MR)) is assessed alongside results of histopathological or cytopathological studies as well as clinical information about a patient. This procedure is called 'triple assessment' in the UK. We have undertaken a project to develop a multiple ontology-based medical image-annotation and reasoning system to support this procedure. Our system integrates image-annotation tools for drawing, image analysis and feature extraction, with ontologies compliant with the proposed language standard, namely OWL. This integration is carried out by the mapping between images and instances in the ontologies. In this paper, we outline the ambit of the project in further detail and discuss some of the architecture and design issues that we have resolved in order to make our system modular and semantic web-enabled. The resulting knowledge base should not only support medical practitioners in the triple assessment process but also provide a resource from which personalised patient information could be delivered via the web direct to patient or care provider. Finally, we describe the progress that we have made thus far on the implementation of this system.
triple assessment, breast cancer screening, ontologies, medical image annotation, virtual primary healthcare, healthcare technology, imaging modalities, x-ray, ultrasound, magnetic resonance, patient information, diagnostics, histopathological studies, cytopathological studies, image analysis, feature extraction, semantic web, knowledge based systems, kbs, e-healthcare, electronic healthcare
1368-2156
403-420
Dasmahapatra, Srinandan
6716035c-8073-4e52-939f-c957bd3a5b7d
Dupplaw, David
f4d583de-bf0d-4bf9-924c-d4bf6fa2a3a5
Hu, Bo
927680e6-b2b4-4b88-9a6e-20a86bb9d2d2
Lewis, Paul
7592e11c-043e-44f0-a9c2-d9c9798e9e8b
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Lewis, Hugh
e9048cd8-c188-49cb-8e2a-45f6b316336a
Dasmahapatra, Srinandan
6716035c-8073-4e52-939f-c957bd3a5b7d
Dupplaw, David
f4d583de-bf0d-4bf9-924c-d4bf6fa2a3a5
Hu, Bo
927680e6-b2b4-4b88-9a6e-20a86bb9d2d2
Lewis, Paul
7592e11c-043e-44f0-a9c2-d9c9798e9e8b
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Lewis, Hugh
e9048cd8-c188-49cb-8e2a-45f6b316336a

Dasmahapatra, Srinandan, Dupplaw, David, Hu, Bo, Lewis, Paul, Shadbolt, Nigel and Lewis, Hugh (2006) Facilitating multi-disciplinary, knowledge-based support for breast cancer screening. International Journal of Healthcare Technology and Management, 7 (5), 403-420.

Record type: Article

Abstract

In order to increase the accuracy of breast cancer screening, the diagnostics of imaging modalities (X-ray, ultrasound or magnetic resonance (MR)) is assessed alongside results of histopathological or cytopathological studies as well as clinical information about a patient. This procedure is called 'triple assessment' in the UK. We have undertaken a project to develop a multiple ontology-based medical image-annotation and reasoning system to support this procedure. Our system integrates image-annotation tools for drawing, image analysis and feature extraction, with ontologies compliant with the proposed language standard, namely OWL. This integration is carried out by the mapping between images and instances in the ontologies. In this paper, we outline the ambit of the project in further detail and discuss some of the architecture and design issues that we have resolved in order to make our system modular and semantic web-enabled. The resulting knowledge base should not only support medical practitioners in the triple assessment process but also provide a resource from which personalised patient information could be delivered via the web direct to patient or care provider. Finally, we describe the progress that we have made thus far on the implementation of this system.

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More information

Published date: 2006
Keywords: triple assessment, breast cancer screening, ontologies, medical image annotation, virtual primary healthcare, healthcare technology, imaging modalities, x-ray, ultrasound, magnetic resonance, patient information, diagnostics, histopathological studies, cytopathological studies, image analysis, feature extraction, semantic web, knowledge based systems, kbs, e-healthcare, electronic healthcare

Identifiers

Local EPrints ID: 23733
URI: https://eprints.soton.ac.uk/id/eprint/23733
ISSN: 1368-2156
PURE UUID: ec6146b7-bead-4ea7-85d9-1616a444964a

Catalogue record

Date deposited: 17 Mar 2006
Last modified: 17 Jul 2017 16:16

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