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Overview of the ImageCLEFmed 2008 Medical Image Retrieval Task [chapter]

Henning Müller, Jayashree Kalpathy-Cramer, Charles E. Kahn, William Hatt, Steven Bedrick, William Hersh
2009 Lecture Notes in Computer Science  
2008 was the fifth year for the medical image retrieval task of ImageCLEF, one of the most popular tracks within CLEF. Participation continued to increase in 2008.  ...  The most significant change in 2008 was the use of a new database containing images from the medical literature.  ...  The images for the 2008 ImageCLEFmed challenge were contributed by the Radiological Society of North America (RSNA).  ... 
doi:10.1007/978-3-642-04447-2_63 fatcat:pvscaefj2nfphmo735elon7fa4

Shangri-La: A medical case-based retrieval tool

Alba G. Seco de Herrera, Roger Schaer, Henning Müller
2017 Journal of the Association for Information Science and Technology  
The approach is evaluated using the ImageCLEFmed 2013 medical retrieval benchmark and can thus be compared to other approaches.  ...  Information retrieval systems are a useful tool to provide access to these documents/images in the biomedical literature related to information needs of medical professionals.  ...  the approaches of the medical case-based retrieval task when using only text on the ImageCLEFmed 2013 collection.  ... 
doi:10.1002/asi.23858 fatcat:l67hfolmtrgsbpjmzjp2qrypje

UB at ImageCLEFmed 2006 [chapter]

Miguel E. Ruiz
2007 Lecture Notes in Computer Science  
The parameters for retrieval feedback and for the linear combination of the generalized vector space model were tuned using queries for the 2008 CLEF medical image retrieval task (imageCLEFmed).  ...  For this year our team participated in the medical image retrieval task.  ...  We used the SMART retrieval system (Salton, 1971 ) for handling the text retrieval part of this task and the GNU Image Finding Tool (GIFT) for performing content-based image retrieval .  ... 
doi:10.1007/978-3-540-74999-8_87 fatcat:tnmctq5dcbhktegzd2bdmsjvo4

MIRACLE at ImageCLEFmed 2008: Semantic vs. Statistical Strategies for Topic Expansion [chapter]

Sara Lana-Serrano, Julio Villena-Román, José Carlos González-Cristóbal
2009 Lecture Notes in Computer Science  
This paper describes the participation of MIRACLE research consortium at the ImageCLEFmed task of ImageCLEF 2009.  ...  and indexing and retrieval.  ...  Acknowledgements This work has been partially supported by the Spanish R+D National Plan, by means of the project BRAVO (Multilingual and Multimodal Answers Advanced Search -Information Retrieval), TIN2007  ... 
doi:10.1007/978-3-642-04447-2_91 fatcat:2ekrffsasvhb3ixnsrftvo7cam

ImageCLEF 2013: The Vision, the Data and the Open Challenges [chapter]

Barbara Caputo, Henning Muller, Bart Thomee, Mauricio Villegas, Roberto Paredes, David Zellhofer, Herve Goeau, Alexis Joly, Pierre Bonnet, Jesus Martinez Gomez, Ismael Garcia Varea, Miguel Cazorla
2013 Lecture Notes in Computer Science  
This paper presents an overview of the ImageCLEF 2013 lab.  ...  The 2013 edition consisted of three tasks: the photo annotation and retrieval task, the plant identification task and the robot vision task.  ...  -Ad-hoc image-based retrieval: This is the classic medical retrieval task, similar to those in organized since 2004.  ... 
doi:10.1007/978-3-642-40802-1_26 fatcat:wi5nqtvoxbch3jtl2u7qzwo5fm

Effectiveness of global features for automatic medical image classification and retrieval – The experiences of OHSU at ImageCLEFmed

Jayashree Kalpathy-Cramer, William Hersh
2008 Pattern Recognition Letters  
The goal of the automatic annotation task was to classify 1000 test images based on the Image Retrieval in Medical Applications (IRMA) code, given a set of 10,000 training images.  ...  In 2006 and 2007, Oregon Health & Science University (OHSU) participated in the automatic image annotation task for medical images at ImageCLEF, an annual international benchmarking event that is part  ...  Acknowledgments We acknowledge the support of NLM Training Grant 1T15 LM009461 and NSF Grant ITR-0325160. Kalpathy-Cramer and Hersh  ... 
doi:10.1016/j.patrec.2008.05.013 pmid:19884953 pmcid:PMC2598732 fatcat:v2my5yhr2nbcdc2radrbw2jota

Comparing the quality of accessing medical literature using content-based visual and textual information retrieval

Henning Müller, Jayashree Kalpathy-Cramer, Charles E. Kahn, Jr., William Hersh, Khan M. Siddiqui, Brent J. Liu
2009 Medical Imaging 2009: Advanced PACS-based Imaging Informatics and Therapeutic Applications  
This article describes the results of the medical image retrieval task of the ImageCLEF 2008 evaluation campaign.  ...  Content-based visual information (or image) retrieval (CBIR) has been an extremely active research domain within medical imaging over the past ten years, with the goal of improving the management of visual  ...  As part of ImageCLEFmed, a medical image retrieval task has started in 2004 16, 19, 20 and a medical image classification task in 2005 21, 22 based on a dataset of the IRMA (Image Retrieval in Medical  ... 
doi:10.1117/12.811416 fatcat:pvkxymulzbd4nnjhivv7fzcpye

A study on the relevance criteria for medical images

Shahram Sedghi, Mark Sanderson, Paul Clough
2008 Pattern Recognition Letters  
In addition, we have investigated the coverage of relevance criteria to search statements from the medical track of ImageCLEF (ImageCLEFMed).  ...  This paper reports the results of a study investigating the relevance criteria used by health care professionals when seeking medical images.  ...  • What is the coverage of the identified criteria in topics used in a large-scale evaluation of medical image retrieval systems (ImageCLEFMed)?  ... 
doi:10.1016/j.patrec.2008.07.003 fatcat:tb7fznkpgja67hbxkdauflt6yi

An Approach toward the Efficient Indexing and Retrieval on Medical X-Ray Images

Sumathi Ganesan, T. S. Subashini
2013 International Journal of Computer Applications  
This paper proposes a system for content based image retrieval of X-ray images.The six classes of X-ray images used for this work are from the IRMA ImageCLEFmed 2008 database.  ...  Today content-based image retrieval (CBIR) has become one of the most active areas of research in computer vision.  ...  The X-ray images used for this work are from the IRMA ImageCLEFmed 2008 database.  ... 
doi:10.5120/13297-0730 fatcat:zsf5r3gilrhsneuldxdz5cdtyy

Multi-Relation Modeling on Multi Concept Extraction LIG participation at ImageClefMed

Loïc Maisonnasse, Éric Gaussier, Jean-Pierre Chevallet
2008 Conference and Labs of the Evaluation Forum  
This paper presents the LIG contribution to the CLEF 2008 medical retrieval task (i.e. ImageCLEFmed).  ...  On ImageCLEFmed our model makes use of the textual part of the corpus and of the medical knowledge found in the Unified Medical Language System (UMLS) knowledge sources.  ...  We then describe the graph extraction process used for documents and queries, and finally we present the different results obtained on the CLEF 2008 medical retrieval task.  ... 
dblp:conf/clef/MaisonnasseGC08 fatcat:rpjhnp3rcbam7hdojsrgc52uqq

Overview of the CLEF 2009 Medical Image Retrieval Track [chapter]

Henning Müller, Jayashree Kalpathy–Cramer, Ivan Eggel, Steven Bedrick, Saïd Radhouani, Brian Bakke, Charles E. Kahn, William Hersh
2010 Lecture Notes in Computer Science  
2009 was the sixth year for the ImageCLEF medical retrieval task.  ...  Medical image retrieval, image retrieval, multimodal retrieval 1 2  ...  We would like to thank the RSNA for supplying the images of their journals Radiology and Radiographics for the ImageCLEF campaign.  ... 
doi:10.1007/978-3-642-15751-6_8 fatcat:abrmk3557nbbdhams4trskydl4

Methods for Combining Content-Based and Textual-Based Approaches in Medical Image Retrieval [chapter]

Mouna Torjmen, Karen Pinel-Sauvagnat, Mohand Boughanem
2009 Lecture Notes in Computer Science  
This paper describes our participation in the Medical Image Retrieval task of Image CLEF 2008. Our aim was to evaluate different combination methods for purely textual and visual approaches.  ...  Our most interesting conclusion is that combining results provided by both methods using classical combination function allows to obtain higher retrieval accuracy in terms of MAP .  ...  In section 3, we present an empirical evaluation of the proposed methods carried out using the Medical Retrieval Task in Image CLEF 2008.  ... 
doi:10.1007/978-3-642-04447-2_87 fatcat:chqnh3xdjzh57dovtdzckelpea

The MedGIFT Group at ImageCLEF 2008 [chapter]

Xin Zhou, Julien Gobeill, Henning Müller
2009 Lecture Notes in Computer Science  
This article describes the participation of the MedGIFT research group at the 2008 ImageCLEFmed image retrieval benchmark. We concentrated on the two tasks concerning medical imaging.  ...  GIFT can be seen as a baseline for the visual retrieval as it has been used for the past five years in ImageCLEF.  ...  Acknowledgments This study was partially supported by the Swiss National Science Foundation (Grant 200020-118638/1), the HES SO with the BeMeVIS project, and the European Union in the 6th Framework Program  ... 
doi:10.1007/978-3-642-04447-2_90 fatcat:i7uuiuo335fqhnx5tjdjafzcce

Evaluating performance of biomedical image retrieval systems—An overview of the medical image retrieval task at ImageCLEF 2004–2013

Jayashree Kalpathy-Cramer, Alba García Seco de Herrera, Dina Demner-Fushman, Sameer Antani, Steven Bedrick, Henning Müller
2015 Computerized Medical Imaging and Graphics  
Medical(image(retrieval(and(classification(have(been(extremely(active(research(topics(over( the( past( 15( years.( With( the( ImageCLEF( benchmark( in( medical( image( retrieval( and( classification( a  ...  important(for(the(evaluation(to(be(close(to(real(world(in( its( size( and( scope.( The( ImageCLEF 1 (medical( retrieval( tasks( have( provided( such( an(  ...  (techniques.( ( Figure*3*Total*runs*submitted*for*the*medical*task* ( Overview*of*participant*methods( Textual!  ... 
doi:10.1016/j.compmedimag.2014.03.004 pmid:24746250 pmcid:PMC4177510 fatcat:xuck5guwojexviqczz4keargjm

Discriminative cue integration for medical image annotation

Tatiana Tommasi, Francesco Orabona, Barbara Caputo
2008 Pattern Recognition Letters  
We tested our methods on the IRMA database, and with two of the three approaches proposed here we participated in the 2007 ImageCLEFmed benchmark evaluation, in the medical image annotation track.  ...  Experiments using the third approach also confirm the power of cue integration for this task.  ...  Regarding the medical image annotation field, in 2006 three groups proposed cue integration methods for the ImageCLEFmed annotation task.  ... 
doi:10.1016/j.patrec.2008.03.009 fatcat:4olpbbfckzaita736b3msu6z3q
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