ArticleJournal of digital imaging2008
Extended query refinement for medical image retrieval.
Article in Journal of digital imaging, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Fifty years of SPIE Medical Imaging proceedings papers.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images.International journal of computer assisted radiology and surgery · 2013Article
- Web-based bone age assessment by content-based image retrieval for case-based reasoning.International journal of computer assisted radiology and surgery · 2012Article
- Towards a repository for standardized medical image and signal case data annotated with ground truth.Journal of digital imaging · 2012Article
- Towards case-based medical learning in radiological decision making using content-based image retrieval.BMC medical informatics and decision making · 2011Article
- Content-based image retrieval applied to BI-RADS tissue classification in screening mammography.World journal of radiology · 2011Article
- Prototypes for content-based image retrieval in clinical practice.The open medical informatics journal · 2011Article
- Computer-Aided Diagnosis in Mammography Using Content-based Image Retrieval Approaches: Current Status and Future Perspectives.Algorithms · 2009Article
- Ontology of gaps in content-based image retrieval.Journal of digital imaging · 2009Article
- Content-Based Image Retrieval in Medicine: Retrospective Assessment, State of the Art, and Future Directions.International journal of healthcare information systems and informatics : official publication of the Information Resources Management Association · 2009Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.