naa a22 4500 510807143 CHVBK 20180411083423.0 cr unu---uuuuu 180411e20131101xx s 000 0 eng 10.1007/s11548-013-0896-5 doi (NATIONALLICENCE)springer-10.1007/s11548-013-0896-5 Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images [Elektronische Daten] [Ashnil Kumar, Jinman Kim, Lei Bi, Michael Fulham, Dagan Feng] Purpose Content-based image retrieval (CBIR) in medicine has been demonstrated to improve evidence-based diagnosis, education, and teaching. However, the low clinical adoption of CBIR is partially because the focus of most studies has been the development of feature extraction and similarity measurement algorithms with limited work on facilitating better understanding of the similarity between complex volumetric and multi-modality medical images. In this paper, we present a method for defining user interfaces (UIs) that enable effective human user interpretation of retrieved images. Methods We derived a set of visualisation and interaction requirements based on the characteristics of modern volumetric medical images. We implemented a UI that visualised multiple views of a single image, displayed abstractions of image data, and provided access to supplementary non-image data. We also defined interactions for refining the search and visually indicating the similarities between images. We applied the UI for the retrieval of multi-modality positron emission tomography and computed tomography (PET-CT) images. We conducted a user survey to evaluate the capabilities of our UI. Results Our proposed method obtained a high rating ( $$\ge $$ 4 out of 5) in the majority of survey questions. In particular, the survey responses indicated the UI presented all the information necessary to understand the retrieved images, and did so in an intuitive manner. Conclusion Our proposed UI design improved the ability of users to interpret and understand the similarity between retrieved PET-CT images. The implementation of CBIR UIs designed to assist human interpretation could facilitate wider adoption of medical CBIR systems. CARS, 2013 Content-based image retrieval nationallicence Retrieval interpretation nationallicence User interface nationallicence PET-CT nationallicence CBIR : Content-based image retrieval nationallicence CT : Computed tomography nationallicence PACS : Picture archiving and communications systems nationallicence PET : Positron emission tomography nationallicence PET-CT : Combined positron emission tomography and computed tomography nationallicence Kumar Ashnil Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut Kim Jinman Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut Bi Lei Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut Fulham Michael Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut Feng Dagan Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/6(2013-11-01), 1003-1014 1861-6410 8:6<1003 2013 8 11548 https://doi.org/10.1007/s11548-013-0896-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-013-0896-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Kumar Ashnil Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut NATIONALLICENCE 700 1- Kim Jinman Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut NATIONALLICENCE 700 1- Bi Lei Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut NATIONALLICENCE 700 1- Fulham Michael Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut NATIONALLICENCE 700 1- Feng Dagan Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/6(2013-11-01), 1003-1014 1861-6410 8:6<1003 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer