Literature DB >> 15888631

Informatics in radiology (infoRAD): benefits of content-based visual data access in radiology.

Henning Müller1, Antoine Rosset, Arnaud Garcia, Jean-Paul Vallée, Antoine Geissbuhler.   

Abstract

The field of medicine is often cited as an area for which content-based visual retrieval holds considerable promise. To date, very few visual image retrieval systems have been used in clinical practice; the first applications of image retrieval systems in medicine are currently being developed to complement conventional text-based searches. An image retrieval system was developed and integrated into a radiology teaching file system, and the performance of the retrieval system was evaluated, with use of query topics that represent the teaching database well, against a standard of reference generated by a radiologist. The results of this evaluation indicate that content-based image retrieval has the potential to become an important technology for the field of radiology, not only in research, but in teaching and diagnostics as well. However, acceptance of this technology in the clinical domain will require identification and implementation of clinical applications that use content-based access mechanisms, necessitating close cooperation between medical practitioners and medical computer scientists. Nevertheless, content-based image retrieval has the potential to become an important technology for radiology practice.

Mesh:

Year:  2005        PMID: 15888631     DOI: 10.1148/rg.253045071

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  15 in total

1.  An interactive system for computer-aided diagnosis of breast masses.

Authors:  Xingwei Wang; Lihua Li; Wei Liu; Weidong Xu; Dror Lederman; Bin Zheng
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

2.  Content-based image retrieval in radiology: analysis of variability in human perception of similarity.

Authors:  Jessica Faruque; Christopher F Beaulieu; Jarrett Rosenberg; Daniel L Rubin; Dorcas Yao; Sandy Napel
Journal:  J Med Imaging (Bellingham)       Date:  2015-04-03

3.  Ontology of gaps in content-based image retrieval.

Authors:  Thomas M Deserno; Sameer Antani; Rodney Long
Journal:  J Digit Imaging       Date:  2008-02-01       Impact factor: 4.056

4.  Optimization of reference library used in content-based medical image retrieval scheme.

Authors:  Sang Cheol Park; Rahul Sukthankar; Lily Mummert; Mahadev Satyanarayanan; Bin Zheng
Journal:  Med Phys       Date:  2007-11       Impact factor: 4.071

5.  Improving performance of content-based image retrieval schemes in searching for similar breast mass regions: an assessment.

Authors:  Xiao-Hui Wang; Sang Cheol Park; Bin Zheng
Journal:  Phys Med Biol       Date:  2009-01-16       Impact factor: 3.609

Review 6.  Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data.

Authors:  Ashnil Kumar; Jinman Kim; Weidong Cai; Michael Fulham; Dagan Feng
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

7.  Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis.

Authors:  Petra Welter; Jörg Riesmeier; Benedikt Fischer; Christoph Grouls; Christiane Kuhl; Thomas M Deserno
Journal:  J Am Med Inform Assoc       Date:  2011 Jul-Aug       Impact factor: 4.497

8.  Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images.

Authors:  Ashnil Kumar; Jinman Kim; Lei Bi; Michael Fulham; Dagan Feng
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-05-07       Impact factor: 2.924

9.  A similarity study of content-based image retrieval system for breast cancer using decision tree.

Authors:  Hyun-Chong Cho; Lubomir Hadjiiski; Berkman Sahiner; Heang-Ping Chan; Mark Helvie; Chintana Paramagul; Alexis V Nees
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

10.  Similarity evaluation in a content-based image retrieval (CBIR) CADx system for characterization of breast masses on ultrasound images.

Authors:  Hyun-Chong Cho; Lubomir Hadjiiski; Berkman Sahiner; Heang-Ping Chan; Mark Helvie; Chintana Paramagul; Alexis V Nees
Journal:  Med Phys       Date:  2011-04       Impact factor: 4.071

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.