Histological image retrieval based on semantic content analysis

The demand for automatic recognition and retrieval of medical images for screening, reference, and management is increasing. We present an intelligent content-based image retrieval system called I-Browse, which integrates both iconic and semantic content for histological image analysis. The I-Browse...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on information technology in biomedicine Vol. 7; no. 1; pp. 26 - 36
Main Authors Tang, H.L., Hanka, R., Ip, H.H.S.
Format Journal Article
LanguageEnglish
Published United States IEEE 01.03.2003
Subjects
Biomedical imaging
Computed tomography
Content based retrieval
Diagnostic Imaging
Image analysis
Image databases
Image retrieval
Indexing
Information retrieval
Information Storage and Retrieval
Magnetic resonance imaging
Medical diagnostic imaging
Online AccessGet full text

Cover

More Information
Summary:The demand for automatic recognition and retrieval of medical images for screening, reference, and management is increasing. We present an intelligent content-based image retrieval system called I-Browse, which integrates both iconic and semantic content for histological image analysis. The I-Browse system combines low-level image processing technology with high-level semantic analysis of medical image content through different processing modules in the proposed system architecture. Similarity measures are proposed and their performance is evaluated. Furthermore, as a byproduct of semantic analysis, I-Browse allows textual annotations to be generated for unknown images. As an image browser, apart from retrieving images by image example, it also supports query by natural language.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:1089-7771
1558-0032
DOI:10.1109/TITB.2003.808500