
Proceedings Paper
The oncology medical image database (OMI-DB)Format | Member Price | Non-Member Price |
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Paper Abstract
Many projects to evaluate or conduct research in medical imaging require the large-scale collection of images (both
unprocessed and processed) and associated data. This demand has led us to design and implement a flexible oncology
image repository, which prospectively collects images and data from multiple sites throughout the UK. This Oncology
Medical Image Database (OMI-DB) has been created to support research involving medical imaging and contains
unprocessed and processed medical images, associated annotations and data, and where applicable expert-determined
ground truths describing features of interest. The process of collection, annotation and storage is almost fully automated
and is extremely adaptable, allowing for quick and easy expansion to disparate imaging sites and situations. Initially the
database was developed as part of a large research project in digital mammography (OPTIMAM). Hence the initial focus
has been digital mammography; as a result, much of the work described will focus on this field. However, the OMI -DB
has been designed to support multiple modalities and is extensible and expandable to store any associated data with full
anonymisation. Currently, the majority of associated data is made up of radiological, clinical and pathological annotations
extracted from the UK’s National Breast Screening System (NBSS). In addition to the data, software and systems have
been created to allow expert radiologists to annotate the images with interesting clinical features and provide descriptors
of these features. The data from OMI-DB has been used in several observer studies and more are planned. To date we have
collected 34,104 2D mammography images from 2,623 individuals.
Paper Details
Date Published: 19 March 2014
PDF: 7 pages
Proc. SPIE 9039, Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations, 903906 (19 March 2014); doi: 10.1117/12.2041674
Published in SPIE Proceedings Vol. 9039:
Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations
Maria Y. Law; Tessa S. Cook, Editor(s)
PDF: 7 pages
Proc. SPIE 9039, Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations, 903906 (19 March 2014); doi: 10.1117/12.2041674
Show Author Affiliations
Mark D. Halling-Brown, The Royal Surrey County Hospital NHS Trust (United Kingdom)
P. T. Looney, The Royal Surrey County Hospital NHS Trust (United Kingdom)
M. N. Patel, The Royal Surrey County Hospital NHS Trust (United Kingdom)
P. T. Looney, The Royal Surrey County Hospital NHS Trust (United Kingdom)
M. N. Patel, The Royal Surrey County Hospital NHS Trust (United Kingdom)
L. M. Warren, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
A. Mackenzie, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
K. C. Young, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
Univ. of Surrey (United Kingdom)
A. Mackenzie, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
K. C. Young, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
Published in SPIE Proceedings Vol. 9039:
Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations
Maria Y. Law; Tessa S. Cook, Editor(s)
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