Extended Query Refinement for Medical Image Retrieval
| Autor: | Berthold B. Wein, Henning Schubert, Thomas M. Deserno, Thomas Seidl, Bartosz Plodowski, Klaus Spitzer, Mark Oliver Güld, Hermann Ney |
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| Rok vydání: | 2007 |
| Předmět: |
Diagnostic Imaging
Databases Factual Computer science Information Storage and Retrieval Query language Query optimization computer.software_genre Sensitivity and Specificity Article Pattern Recognition Automated User-Computer Interface Query expansion Software Design Web query classification Computer Graphics Humans Radiology Nuclear Medicine and imaging Query by Example Medical Informatics Applications Image retrieval computer.programming_language Internet Information retrieval Web search query Radiological and Ultrasound Technology Computer Science Applications Radiology Information Systems Radiographic Image Interpretation Computer-Assisted Sargable Data mining computer |
| Zdroj: | Journal of Digital Imaging. 21:280-289 |
| ISSN: | 1618-727X 0897-1889 |
| Popis: | The impact of image pattern recognition on accessing large databases of medical images has recently been explored, and content-based image retrieval (CBIR) in medical applications (IRMA) is researched. At the present, however, the impact of image retrieval on diagnosis is limited, and practical applications are scarce. One reason is the lack of suitable mechanisms for query refinement, in particular, the ability to (1) restore previous session states, (2) combine individual queries by Boolean operators, and (3) provide continuous-valued query refinement. This paper presents a powerful user interface for CBIR that provides all three mechanisms for extended query refinement. The various mechanisms of man–machine interaction during a retrieval session are grouped into four classes: (1) output modules, (2) parameter modules, (3) transaction modules, and (4) process modules, all of which are controlled by a detailed query logging. The query logging is linked to a relational database. Nested loops for interaction provide a maximum of flexibility within a minimum of complexity, as the entire data flow is still controlled within a single Web page. Our approach is implemented to support various modalities, orientations, and body regions using global features that model gray scale, texture, structure, and global shape characteristics. The resulting extended query refinement has a significant impact for medical CBIR applications. |
| Databáze: | OpenAIRE |
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