Content-Based Indexing of Medical Images for Digital Radiology Applications

  • Piotr Boninski
  • Artur Przelaskowski
Part of the Advances in Soft Computing book series (AINSC, volume 47)


This paper concerns content-based image retrieval in medical domain considering the challenges of rapidly growing amounts of medical data, permanent progress of computer-aided radiology and the development of global data exchange networks (like Mammogrid). The aim of featured research was to propose effective content-based image retrieval algorithms in two approaches to that problem. The first is medical images indexing for various modalities, on the assumption that we do not attempt to analyze image semantics. In that approach we try to find the images ’visually similar’ to the given one – with similar organ, modality, orientation, etc. The second approach undertaken in conducted research is medical images indexing with taking into consideration their semantics. Such approach makes use of ’domain knowledge’ about specified modality, examination, giving the opportunity to introduce descriptors of image semantics, especially related to diagnostic content. The methods and algorithms characterized in this paper are both related to various modalities and strictly dedicated to the one modality only - in this research it is mammography. The obtained results show the usefulness of proposed methods.


Salient Region Relevant Image Mammographic Image Semantic Point Pathology Symptom 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Piotr Boninski
    • 1
  • Artur Przelaskowski
    • 1
  1. 1.Warsaw University of Technology 

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