A re-examination of relevance: toward a dynamic, situational definition
Information Processing and Management: an International Journal
3D object recognition using invariance
Artificial Intelligence - Special volume on computer vision
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Communications of the ACM
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Benchmarking for Content-Based Visual Information Search
VISUAL '00 Proceedings of the 4th International Conference on Advances in Visual Information Systems
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Differential Feature Distribution Maps for Image Segmentation and Region Queries in Image Databases
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Classification Error Rate for Quantitative Evaluation of Content-based Image Retrieval Systems
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
TRECVID: evaluating the effectiveness of information retrieval tasks on digital video
Proceedings of the 12th annual ACM international conference on Multimedia
ImageCLEF 2004: combining image and multi-lingual search for medical image retrieval
CLEF'04 Proceedings of the 5th conference on Cross-Language Evaluation Forum: multilingual Information Access for Text, Speech and Images
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Efficient benchmarking of content-based image retrieval via resampling
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
An investigation in applying image retrieval techniques to X-ray engineering pictures
AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Multimodal medical image retrieval OHSU at ImageCLEF 2008
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
The CLEF 2005 cross–language image retrieval track
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
MCBR-CDS'12 Proceedings of the Third MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
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Content--based image retrieval in the medical domain is an extremely hot topic in medical imaging as it promises to help better managing the large amount of medical images being produced. Applications are mainly expected in the field of medical teaching files and for research projects, where performance issues and speed are less critical than in the field of diagnostic aid. Final goal with most impact will be the use as a diagnostic aid in a real--world clinical setting.Other applications of image retrieval and image classification can be the automatic annotation of images with basic concepts or the control of DICOM header information.ImageCLEF is part of the Cross Language Evaluation Forum (CLEF). Since 2004, a medical image retrieval task has been added. Goal is to create databases of a realistic and useful size and also query topics that are based on real--world needs in the medical domain but still correspond to the limited capabilities of purely visual retrieval at the moment. Goal is to direct the research onto real applications and towards real clinical problems to give researchers who are not directly linked to medical facilities a possibility to work on the interesting problem of medical image retrieval based on real data sets and problems. The missing link between computer science research departments and clinical routine is one of the biggest problems that becomes evident when reading much of the current literature on medical image retrieval. Most databases are extremely small, the treated problems often far from clinical reality, and there is no integration of the prototypes into a hospital infrastructure. Only few retrieval articles specifically mention problems related to the DICOM format (Digital Imaging and Communications in Medicine) and the sheer amount of data that needs to be treated in an image archive ( 30.000 images per day in the Geneva radiology).This article develops the various axes that can be taken into account for medical image retrieval system evaluation. First, the axes are developed based on current challenges and experiences from ImageCLEF. Then, the resources developed for ImageCLEF are listed and finally, the application of the axes is explained to show the bases of the ImageCLEFmed evaluation campaign. This article will only concentrate on the medical retrieval tasks, the non-medical tasks will only shortly be mentioned.