Literature DB >> 10342174

Content-based image retrieval in picture archiving and communications systems.

H Qi1, W E Snyder.   

Abstract

We propose the concept of content-based image retrieval (CBIR) and demonstrate its potential use in picture archival and communication system (PACS). We address the importance of image retrieval in PACS and highlight the drawbacks existing in traditional textual-based retrieval. We use a digital mammogram database as our testing data to illustrate the idea of CBIR, where retrieval is carried out based on object shape, size, and brightness histogram. With a user-supplied query image, the system can find images with similar characteristics from the archive, and return them along with the corresponding ancillary data, which may provide a valuable reference for radiologists in a new case study. Furthermore, CBIR can perform like a consultant in emergencies when radiologists are not available. We also show that content-based retrieval is a more natural approach to man-machine communication.

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Mesh:

Year:  1999        PMID: 10342174      PMCID: PMC3452879          DOI: 10.1007/BF03168763

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  10 in total

1.  Towards content-based image retrieval in a HIS-integrated PACS.

Authors:  C Le Bozec; E Zapletal; M C Jaulent; D Heudes; P Degoulet
Journal:  Proc AMIA Symp       Date:  2000

2.  Evaluation of objective similarity measures for selecting similar images of mammographic lesions.

Authors:  Ryohei Nakayama; Hiroyuki Abe; Junji Shiraishi; Kunio Doi
Journal:  J Digit Imaging       Date:  2011-02       Impact factor: 4.056

3.  Adaptive learning for relevance feedback: application to digital mammography.

Authors:  Jung Hun Oh; Yongyi Yang; Issam El Naqa
Journal:  Med Phys       Date:  2010-08       Impact factor: 4.071

4.  Ontology of gaps in content-based image retrieval.

Authors:  Thomas M Deserno; Sameer Antani; Rodney Long
Journal:  J Digit Imaging       Date:  2008-02-01       Impact factor: 4.056

5.  Representation of lesion similarity by use of multidimensional scaling for breast masses on mammograms.

Authors:  Chisako Muramatsu; Kohei Nishimura; Tokiko Endo; Mikinao Oiwa; Misaki Shiraiwa; Kunio Doi; Hiroshi Fujita
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

6.  Usefulness of presentation of similar images in the diagnosis of breast masses on mammograms: comparison of observer performances in Japan and the USA.

Authors:  Chisako Muramatsu; Robert A Schmidt; Junji Shiraishi; Tokiko Endo; Hiroshi Fujita; Kunio Doi
Journal:  Radiol Phys Technol       Date:  2012-08-08

Review 7.  Overview on subjective similarity of images for content-based medical image retrieval.

Authors:  Chisako Muramatsu
Journal:  Radiol Phys Technol       Date:  2018-05-08

8.  Prototypes for content-based image retrieval in clinical practice.

Authors:  Adrien Depeursinge; Benedikt Fischer; Henning Müller; Thomas M Deserno
Journal:  Open Med Inform J       Date:  2011-07-27

9.  Medical image retrieval: past and present.

Authors:  Kyung Hoon Hwang; Haejun Lee; Duckjoo Choi
Journal:  Healthc Inform Res       Date:  2012-03-31

10.  The diagnostic path, a useful visualisation tool in virtual microscopy.

Authors:  Thomas Schrader; Sonja Niepage; Thomas Leuthold; Kai Saeger; Karsten Schluns; Peter Hufnagl; Klaus Kayser; Manfred Dietel
Journal:  Diagn Pathol       Date:  2006-11-08       Impact factor: 2.644

  10 in total

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