Literature DB >> 18214614

POSTGRESQL-IE: an image-handling extension for PostgreSQL.

Denise Guliato1, Ernani V de Melo, Rangaraj M Rangayyan, Robson C Soares.   

Abstract

The last decade witnessed a growing interest in research on content-based image retrieval (CBIR) and related areas. Several systems for managing and retrieving images have been proposed, each one tailored to a specific application. Functionalities commonly available in CBIR systems include: storage and management of complex data, development of feature extractors to support similarity queries, development of index structures to speed up image retrieval, and design and implementation of an intuitive graphical user interface tailored to each application. To facilitate the development of new CBIR systems, we propose an image-handling extension to the relational database management system (RDBMS) PostgreSQL. This extension, called PostgreSQL-IE, is independent of the application and provides the advantage of being open source and portable. The proposed system extends the functionalities of the structured query language SQL with new functions that are able to create new feature extraction procedures, new feature vectors as combinations of previously defined features, and new access methods, as well as to compose similarity queries. PostgreSQL-IE makes available a new image data type, which permits the association of various images with a given unique image attribute. This resource makes it possible to combine visual features of different images in the same feature vector. To validate the concepts and resources available in the proposed extended RDBMS, we propose a CBIR system applied to the analysis of mammograms using PostgreSQL-IE.

Mesh:

Year:  2008        PMID: 18214614      PMCID: PMC3043679          DOI: 10.1007/s10278-007-9097-5

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


  6 in total

1.  Boundary modelling and shape analysis methods for classification of mammographic masses.

Authors:  R M Rangayyan; N R Mudigonda; J E Desautels
Journal:  Med Biol Eng Comput       Date:  2000-09       Impact factor: 2.602

2.  Fractal analysis of contours of breast masses in mammograms.

Authors:  Rangaraj M Rangayyan; Thanh M Nguyen
Journal:  J Digit Imaging       Date:  2007-09       Impact factor: 4.056

3.  Detection of breast masses in mammograms by density slicing and texture flow-field analysis.

Authors:  N R Mudigonda; R M Rangayyan; J E Desautels
Journal:  IEEE Trans Med Imaging       Date:  2001-12       Impact factor: 10.048

4.  Measures of acutance and shape for classification of breast tumors.

Authors:  R M Rangayyan; N M El-Faramawy; J E Desautels; O A Alim
Journal:  IEEE Trans Med Imaging       Date:  1997-12       Impact factor: 10.048

5.  Polygonal modeling of contours of breast tumors with the preservation of spicules.

Authors:  Denise Guliato; Rangaraj M Rangayyan; Juliano D Carvalho; Sérgio A Santiago
Journal:  IEEE Trans Biomed Eng       Date:  2008-01       Impact factor: 4.538

6.  Spiculation-preserving polygonal modeling of contours of breast tumors.

Authors:  Denise Guliato; Rangaraj M Rangayyan; Juliano Daloia de Carvalho; Sérgio Anchieta Santiago
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2006
  6 in total
  2 in total

1.  INDIAM--an e-learning system for the interpretation of mammograms.

Authors:  Denise Guliato; Ricardo S Bôaventura; Marcelo A Maia; Rangaraj M Rangayyan; Mariângela S Simedo; Túlio A A Macedo
Journal:  J Digit Imaging       Date:  2008-04-19       Impact factor: 4.056

2.  Design of a Web-tool for diagnostic clinical trials handling medical imaging research.

Authors:  Alicia Baltasar Sánchez; Angel González-Sistal
Journal:  J Digit Imaging       Date:  2011-04       Impact factor: 4.056

  2 in total

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