RESEARCH ARTICLE


The State of the Art of Medical Imaging Technology: from Creation to Archive and Back



Xiaohong W Gao*, 1, Yu Qian 1, Rui Hui 1, 2
1 School of Engineering and Information Sciences, Middlesex University, London, NW4 4BT, UK
2 Department of Neurosurgery, General Navy Hospital, Beijing, P.R. China


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© Gao et al.; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the School of Engineering and Information Sciences, Middlesex University, London, NW4 4BT, UK; Tel: +44 (0) 20 8411 Fax: +44 (0) 20 8411 2252; Email: x.gao@mdx.ac.uk


Abstract

Medical imaging has learnt itself well into modern medicine and revolutionized medical industry in the last 30 years. Stemming from the discovery of X-ray by Nobel laureate Wilhelm Roentgen, radiology was born, leading to the creation of large quantities of digital images as opposed to film-based medium. While this rich supply of images provides immeasurable information that would otherwise not be possible to obtain, medical images pose great challenges in archiving them safe from corrupted, lost and misuse, retrievable from databases of huge sizes with varying forms of metadata, and reusable when new tools for data mining and new media for data storing become available. This paper provides a summative account on the creation of medical imaging tomography, the development of image archiving systems and the innovation from the existing acquired image data pools. The focus of this paper is on content-based image retrieval (CBIR), in particular, for 3D images, which is exemplified by our developed online e-learning system, MIRAGE, home to a repository of medical images with variety of domains and different dimensions. In terms of novelties, the facilities of CBIR for 3D images coupled with image annotation in a fully automatic fashion have been developed and implemented in the system, resonating with future versatile, flexible and sustainable medical image databases that can reap new innovations.

Keywords: 3D image retrieval, CBIR, medical imaging techniques, texture-based retrieval, PACS, e-learning.