Literature DB >> 9147338

Medical image databases: a content-based retrieval approach.

H D Tagare1, C C Jaffe, J Duncan.   

Abstract

Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema.

Mesh:

Year:  1997        PMID: 9147338      PMCID: PMC61234          DOI: 10.1136/jamia.1997.0040184

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


  11 in total

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Authors:  S Zink; C C Jaffe
Journal:  Invest Radiol       Date:  1993-04       Impact factor: 6.016

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Authors:  B F Bohren; M Hadzikadic; E N Hanley
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10.  Functional left ventricular aneurysm formation after acute anterior transmural myocardial infarction. Incidence, natural history, and prognostic implications.

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  23 in total

1.  PathMaster: content-based cell image retrieval using automated feature extraction.

Authors:  M E Mattie; L Staib; E Stratmann; H D Tagare; J Duncan; P L Miller
Journal:  J Am Med Inform Assoc       Date:  2000 Jul-Aug       Impact factor: 4.497

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Authors:  C LeBozec; E Zapletal; P Degoulet; M C Jaulent
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3.  The Stanford MediaServer Project: strategies for building a flexible digital media platform to support biomedical education and research.

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4.  Extended query refinement for medical image retrieval.

Authors:  Thomas M Deserno; Mark O Güld; Bartosz Plodowski; Klaus Spitzer; Berthold B Wein; Henning Schubert; Hermann Ney; Thomas Seidl
Journal:  J Digit Imaging       Date:  2007-05-12       Impact factor: 4.056

5.  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

6.  Imaging-based observational databases for clinical problem solving: the role of informatics.

Authors:  Alex A T Bui; William Hsu; Corey Arnold; Suzie El-Saden; Denise R Aberle; Ricky K Taira
Journal:  J Am Med Inform Assoc       Date:  2013-06-17       Impact factor: 4.497

Review 7.  Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data.

Authors:  Ashnil Kumar; Jinman Kim; Weidong Cai; Michael Fulham; Dagan Feng
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

8.  B-SPID: an object-relational database architecture to store, retrieve, and manipulate neuroimaging data.

Authors:  B Diallo; F Dolidon; J M Travere; B Mazoyer
Journal:  Hum Brain Mapp       Date:  1999       Impact factor: 5.038

9.  Content-based image retrieval applied to BI-RADS tissue classification in screening mammography.

Authors:  Júlia Epischina Engrácia de Oliveira; Arnaldo de Albuquerque Araújo; Thomas M Deserno
Journal:  World J Radiol       Date:  2011-01-28

10.  Medical imaging informatics: challenges of definition and integration.

Authors:  C A Kulikowski
Journal:  J Am Med Inform Assoc       Date:  1997 May-Jun       Impact factor: 4.497

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