Literature DB >> 24491269

DCMDSM: a DICOM decomposed storage model.

Alexandre Savaris1, Theo Härder2, Aldo von Wangenheim3.   

Abstract

OBJECTIVE: To design, build, and evaluate a storage model able to manage heterogeneous digital imaging and communications in medicine (DICOM) images. The model must be simple, but flexible enough to accommodate variable content without structural modifications; must be effective on answering query/retrieval operations according to the DICOM standard; and must provide performance gains on querying/retrieving content to justify its adoption by image-related projects.
METHODS: The proposal adapts the original decomposed storage model, incorporating structural and organizational characteristics present in DICOM image files. Tag values are stored according to their data types/domains, in a schema built on top of a standard relational database management system (RDBMS). Evaluation includes storing heterogeneous DICOM images, querying metadata using a variable number of predicates, and retrieving full-content images for different hierarchical levels. RESULTS AND DISCUSSION: When compared to a well established DICOM image archive, the proposal is 0.6-7.2 times slower in storing content; however, in querying individual tags, it is about 48.0% faster. In querying groups of tags, DICOM decomposed storage model (DCMDSM) is outperformed in scenarios with a large number of tags and low selectivity (being 66.5% slower); however, when the number of tags is balanced with better selectivity predicates, the performance gains are up to 79.1%. In executing full-content retrieval, in turn, the proposal is about 48.3% faster.
CONCLUSIONS: DCMDSM is a model built for the storage of heterogeneous DICOM content, based on a straightforward database design. The results obtained through its evaluation attest its suitability as a storage layer for projects where DICOM images are stored once, and queried/retrieved whenever necessary. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Keywords:  Database Management Systems; Decomposed Storage Model; Digital Imaging and Communications in Medicine; Information Storage and Retrieval

Mesh:

Year:  2014        PMID: 24491269      PMCID: PMC4147623          DOI: 10.1136/amiajnl-2013-002337

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  10 in total

1.  Introduction to the DICOM standard.

Authors:  Peter Mildenberger; Marco Eichelberg; Eric Martin
Journal:  Eur Radiol       Date:  2001-09-15       Impact factor: 5.315

2.  Predicting the fidelity of JPEG2000 compressed CT images using DICOM header information.

Authors:  Kil Joong Kim; Bohyoung Kim; Hyunna Lee; Hosik Choi; Jong-June Jeon; Jeong-Hwan Ahn; Kyoung Ho Lee
Journal:  Med Phys       Date:  2011-12       Impact factor: 4.071

3.  Managing biomedical image metadata for search and retrieval of similar images.

Authors:  Daniel Korenblum; Daniel Rubin; Sandy Napel; Cesar Rodriguez; Chris Beaulieu
Journal:  J Digit Imaging       Date:  2011-08       Impact factor: 4.056

4.  Dynamic tables: an architecture for managing evolving, heterogeneous biomedical data in relational database management systems.

Authors:  John Corwin; Avi Silberschatz; Perry L Miller; Luis Marenco
Journal:  J Am Med Inform Assoc       Date:  2006-10-26       Impact factor: 4.497

5.  Automatic computed tomography patient dose calculation using DICOM header metadata.

Authors:  A Jahnen; S Kohler; J Hermen; D Tack; C Back
Journal:  Radiat Prot Dosimetry       Date:  2011-08-09       Impact factor: 0.972

6.  Automated detection of changes in patient exposure in digital projection radiography using exposure index from DICOM header metadata.

Authors:  Hans-Erik Källman; Erik Halsius; Mikael Folkesson; Ylva Larsson; Mats Stenström; Magnus Båth
Journal:  Acta Oncol       Date:  2011-08       Impact factor: 4.089

Review 7.  Understanding and using DICOM, the data interchange standard for biomedical imaging.

Authors:  W D Bidgood; S C Horii; F W Prior; D E Van Syckle
Journal:  J Am Med Inform Assoc       Date:  1997 May-Jun       Impact factor: 4.497

8.  Extraction of CT dose information from DICOM metadata: automated Matlab-based approach.

Authors:  Jaydev K Dave; Eric L Gingold
Journal:  AJR Am J Roentgenol       Date:  2013-01       Impact factor: 3.959

9.  Development and evaluation of a low-cost and high-capacity DICOM image data storage system for research.

Authors:  Masahiro Yakami; Koichi Ishizu; Takeshi Kubo; Tomohisa Okada; Kaori Togashi
Journal:  J Digit Imaging       Date:  2010-02-24       Impact factor: 4.056

10.  OSPACS: Ultrasound image management system.

Authors:  Will Stott; Andy Ryan; Ian J Jacobs; Usha Menon; Conrad Bessant; Christopher Jones
Journal:  Source Code Biol Med       Date:  2008-06-20
  10 in total
  1 in total

1.  The Challenges of Implementing Comprehensive Clinical Data Warehouses in Hospitals.

Authors:  François Bocquet; Mario Campone; Marc Cuggia
Journal:  Int J Environ Res Public Health       Date:  2022-06-16       Impact factor: 4.614

  1 in total

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