title: Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images.
abstract: OBJECTIVE
  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 ( ≥ 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.
  
  
  CONCLUSIONS
  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.
authors: Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Sydney, Australia, ashnil@it.usyd.edu.au.
authors: Ashnil
authors: A
authors: Kumar
authors: Jinman
authors: J
authors: Kim
authors: Lei
authors: L
authors: Bi
authors: Michael
authors: M
authors: Fulham
authors: Dagan
authors: D
authors: Feng
mesh_terms: D000465:Algorithms; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval; D064847:Multimodal Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods; D014584:User-Computer Interface
references: Med Image Anal. 2010 Apr;14(2):227-41
references: 20007020
references: J Digit Imaging. 2009 Apr;22(2):202-15
references: 18239964
references: Int J Radiat Oncol Biol Phys. 2004 May 1;59(1):78-86
references: 15093902
references: IEEE Trans Inf Technol Biomed. 2010 Sep;14(5):1227-35
references: 20813626
references: Int J Healthc Inf Syst Inform. 2009 Jan 1;4(1):1-16
references: 20523757
references: Int J Med Inform. 2009 Apr;78 Suppl 1:S13-24
references: 18996737
references: Int J Med Inform. 2004 Feb;73(1):1-23
references: 15036075
references: IEEE Trans Vis Comput Graph. 2004 Jan-Feb;10(1):72-84
references: 15382699
references: J Digit Imaging. 2008 Sep;21(3):280-9
references: 17497197
references: IEEE Trans Med Imaging. 2011 Jan;30(1):108-18
references: 20693107
references: Radiology. 2003 Jul;228(1):265-70
references: 12832587
references: Semin Nucl Med. 2003 Jul;33(3):193-204
references: 12931321
references: Radiology. 2007 Sep;244(3):807-14
references: 17709830
references: Radiology. 2007 Feb;242(2):360-85
references: 17255408
references: IEEE Trans Med Imaging. 2001 Jun;20(6):490-8
references: 11437109
references: Radiology. 2010 Jul;256(1):243-52
references: 20505065
references: Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:5408-11
references: 23367152
references: Radiographics. 2005 May-Jun;25(3):849-58
references: 15888631