Literature DB >> 18720055

DICOM Metadata repository for technical information in digital medical images.

Hans-Erik Källman1, Erik Halsius, Magnus Olsson, Mats Stenström.   

Abstract

UNLABELLED: The diagnostic medical image contains, apart from the pixel data, a detailed description of how the image was produced. The information reveals details on image geometry, radiation data as well as more complex quality index in a varying degree, mostly dependent on the age of the equipment. There is no simple way to retrieve, process and display this data in a general image workstation.
MATERIAL AND METHODS: Since November 2004 a DICOM metadata repository has been used to record image header parameters. The automated data extraction, storage and display are based on simple standard programming and have performed without malfunction since the start, today containing metadata from 18 million images.
RESULTS: The data in the metadata repository has been used in dose optimization for a Computed Radiography image plate system, analyzing the exposure index and making use of the possibilities to organize the data in examinations, projections as well as examination rooms. Analysis of exposure index in the context of these parameters shows promising qualities as it makes detection of dosimetric problems as well as follow-up of dose adjustments simpler. Current work is aimed at creating a vendor independent platform and to further develop methods to support dose optimization for flat panel direct digital detectors and computed tomography (CT) systems. The possibilities to detect equipment malfunction will be further investigated.

Mesh:

Year:  2009        PMID: 18720055     DOI: 10.1080/02841860802258786

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  8 in total

1.  Dicoogle - an open source peer-to-peer PACS.

Authors:  Carlos Costa; Carlos Ferreira; Luís Bastião; Luís Ribeiro; Augusto Silva; José Luís Oliveira
Journal:  J Digit Imaging       Date:  2011-10       Impact factor: 4.056

2.  DICOM Standard Conformance in Veterinary Medicine in Germany: a Survey of Imaging Studies in Referral Cases.

Authors:  Andreas Brühschwein; Julius Klever; Tom Wilkinson; Andrea Meyer-Lindenberg
Journal:  J Digit Imaging       Date:  2018-02       Impact factor: 4.056

3.  Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction?

Authors:  Xiaochuan Pan; Emil Y Sidky; Michael Vannier
Journal:  Inverse Probl       Date:  2009-01-01       Impact factor: 2.407

4.  Deep Learning-based Detection of Intravenous Contrast Enhancement on CT Scans.

Authors:  Zezhong Ye; Jack M Qian; Ahmed Hosny; Roman Zeleznik; Deborah Plana; Jirapat Likitlersuang; Zhongyi Zhang; Raymond H Mak; Hugo J W L Aerts; Benjamin H Kann
Journal:  Radiol Artif Intell       Date:  2022-05-04

5.  Automated Billing Code Retrieval from MRI Scanner Log Data.

Authors:  Jonas Denck; Wilfried Landschütz; Knud Nairz; Johannes T Heverhagen; Andreas Maier; Eva Rothgang
Journal:  J Digit Imaging       Date:  2019-12       Impact factor: 4.056

6.  ALIGNING VIDEO-AND STRUCTURED DATA FOR IMAGING OPTIMISATION.

Authors:  Jonas Ivarsson; Anja Almén; Mårten Falkenberg; Charlotta Lundh; Magnus Båth
Journal:  Radiat Prot Dosimetry       Date:  2021-10-12       Impact factor: 0.954

7.  Understanding Scanner Utilization With Real-Time DICOM Metadata Extraction.

Authors:  Pradeeban Kathiravelu; Ashish Sharma; Puneet Sharma
Journal:  IEEE Access       Date:  2021-01-11       Impact factor: 3.476

Review 8.  Digital radiography exposure indices: A review.

Authors:  Ursula Mothiram; Patrick C Brennan; Sarah J Lewis; Bernadette Moran; John Robinson
Journal:  J Med Radiat Sci       Date:  2014-05-11
  8 in total

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