Filters








78 Hits in 5.7 sec

Baseline Results for the ImageCLEF 2006 Medical Automatic Annotation Task [chapter]

Mark O Güld, Christian Thies, Benedikt Fischer, Thomas M Deserno
2007 Lecture Notes in Computer Science  
This work reports baseline results for the CLEF 2008 Medical Automatic Annotation Task (MAAT) by applying a classifier with a fixed parameter set to all tasks 2005 -2008.  ...  In 2008, the baseline classifier yields error scores of 170.34 and 182.77 for k=1 and k=5 when the full code is reported, which corresponds to error rates of 51.3% and 52.8% for 1-NN and 5-NN, respectively  ...  Introduction In 2008, the Medical Automatic Annotation Task (MAAT) is held for the fourth time as part of the annual challenge issued by the Cross-Language Evaluation Forum (CLEF).  ... 
doi:10.1007/978-3-540-74999-8_84 fatcat:yr6jutpelneenky7oofzlqgcf4

The CLEF 2005 Automatic Medical Image Annotation Task

Thomas Deselaers, Henning Müller, Paul Clough, Hermann Ney, Thomas M. Lehmann
2006 International Journal of Computer Vision  
This paper focuses on the database used, the task setup, and the plans for further medical image annotation tasks in the context of ImageCLEF.  ...  The automatic annotation task was added to ImageCLEF in 2005 and provides the first international evaluation of state-of-the-art methods for completely automatic annotation of medical images based on visual  ...  Furthermore we would like to thank the CLEF campaign for allowing ImageCLEF to be part of it.  ... 
doi:10.1007/s11263-006-0007-y fatcat:a2md6mxs6bahtaecqt2mnleyia

FIRE in ImageCLEF 2005: Combining Content-Based Image Retrieval with Textual Information Retrieval [chapter]

Thomas Deselaers, Tobias Weyand, Daniel Keysers, Wolfgang Macherey, Hermann Ney
2006 Lecture Notes in Computer Science  
The results achieved are very good. In particular, we obtained the first and the third rank in the automatic annotation task out of 44 submissions from 12 groups.  ...  For the medical retrieval task, we combined several low-level image features with textual information retrieval.  ...  We participated in the automatic annotation task and the medical image retrieval task.  ... 
doi:10.1007/11878773_72 fatcat:cgnk3hozt5cvnbo7mg23ditoke

Using heterogeneous annotation and visual information for the benchmarking of image retrieval systems

Henning Müller, Paul Clough, William Hersh, Thomas Deselaers, Thomas M. Lehmann, Bruno Janvier, Antoine Geissbuhler, Simone Santini, Raimondo Schettini, Theo Gevers
2006 Internet Imaging VII  
The ImageCLEF benchmark shows the need for realistic and standardised datasets, search tasks and ground truths for visual information retrieval evaluation.  ...  In particular, we offer a medical retrieval task which models exactly the situation of heterogenous annotation by combining four collections with annotations of varying quality, structure, extent and language  ...  We also acknowledge the support of National Science Foundation (NSF) grant ITR-0325160. The establishment of the IRMA database was funded by the German DFG with grant Le 1108/4.  ... 
doi:10.1117/12.660259 fatcat:6yrpnkatabe5hfi54kmnwajofy

Deformations, patches, and discriminative models for automatic annotation of medical radiographs

Thomas Deselaers, Hermann Ney
2008 Pattern Recognition Letters  
The methods were applied in the medical image annotation tasks of ImageCLEF in 2005, 2006, and 2007.  ...  In this paper, we describe three different methods for the classification and annotation of medical radiographs.  ...  The authors would like to thank Daniel Keysers, Christian Gollan, Andre Hegerath, Tobias Gass, Tobias Weyand for their contributions to this work.  ... 
doi:10.1016/j.patrec.2008.03.013 fatcat:4acprbzqyfchbdxnky3jni3toy

The ImageCLEFmed Medical Image Retrieval Task Test Collection

William Hersh, Henning Müller, Jayashree Kalpathy-Cramer
2008 Journal of digital imaging  
The goal of the ImageCLEF medical image retrieval task (Image-CLEFmed) is to improve understanding and system capability in search for medical images.  ...  We also provide baseline results with the new collection and describe them in the context of past research with portions of the collection.  ...  Instructions for obtaining the data described in this paper can be obtained from the ImageCLEFmed Website (http://ir.ohsu. edu/image/).  ... 
doi:10.1007/s10278-008-9154-8 pmid:18769965 pmcid:PMC3043731 fatcat:msdjjtocxffopbydj7bbwdgwja

Automatic medical image annotation in ImageCLEF 2007: Overview, results, and discussion

Thomas Deselaers, Thomas M. Deserno, Henning Müller
2008 Pattern Recognition Letters  
Since 2005, the medical automatic image annotation task exists in ImageCLEF with increasing complexity to evaluate the performance of state-of-the-art methods for completely automatic annotation of medical  ...  In this paper, the automatic medical annotation task of the 2007 CLEF cross-language image retrieval campaign (ImageCLEF) is described.  ...  Medical Automatic Image Annotation Tasks 2005 and 2006.  ... 
doi:10.1016/j.patrec.2008.03.001 fatcat:zr6dsbf2rnf3bp32phfe7wwreu

The MedGIFT Group at ImageCLEF 2009 [chapter]

Xin Zhou, Ivan Eggel, Henning Müller
2010 Lecture Notes in Computer Science  
The baseline setup used for the past five years already obtained the best result among all our visual submissions. For the medical image annotation task, two approaches were tested.  ...  For the medical image classification task, the GIFT-kNN-based approach gives stable results, although not in the quality of the best groups.  ...  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:10.1007/978-3-642-15751-6_25 fatcat:lvr5cnbfhvcgpb3owkv4wpr3t4

Manual Query Modification and Data Fusion for Medical Image Retrieval [chapter]

Jeffery R. Jensen, William R. Hersh
2006 Lecture Notes in Computer Science  
For the ImageCLEF 2005 medical task, we used a text retrieval system as the foundation of our experiments to assess retrieval of images from the test collection.  ...  Image retrieval has great potential for a variety of tasks in medicine but is currently underdeveloped.  ...  Oregon Health & Science University (OHSU) participated in the medical image retrieval task of ImageCLEF 2005.  ... 
doi:10.1007/11878773_74 fatcat:xjeyjgf4ofa27a3reiybdzyerm

General Overview of ImageCLEF at the CLEF 2015 Labs [chapter]

Mauricio Villegas, Henning Müller, Andrew Gilbert, Luca Piras, Josiah Wang, Krystian Mikolajczyk, Alba G. Seco de Herrera, Stefano Bromuri, M. Ashraful Amin, Mahmood Kazi Mohammed, Burak Acar, Suzan Uskudarli (+3 others)
2015 Lecture Notes in Computer Science  
In 2016, the 14th edition of ImageCLEF, three main tasks were proposed: 1) identification, multi-label classification and separation of compound figures from biomedical literature; 2) automatic annotation  ...  ImageCLEF is an ongoing initiative that promotes the evaluation of technologies for annotation, indexing and retrieval for providing information access to collections of images in various usage scenarios  ...  Acknowledgements The general coordination and the handwritten retrieval task have been supported by the European Union (EU) Horizon 2020 grant READ (Recognition and Enrichment of Archival Documents) (Ref  ... 
doi:10.1007/978-3-319-24027-5_45 fatcat:c5r3lw7ssjhlrpvupjbr4eqazy

General Overview of ImageCLEF at the CLEF 2016 Labs [chapter]

Mauricio Villegas, Henning Müller, Alba García Seco de Herrera, Roger Schaer, Stefano Bromuri, Andrew Gilbert, Luca Piras, Josiah Wang, Fei Yan, Arnau Ramisa, Emmanuel Dellandrea, Robert Gaizauskas (+5 others)
2016 Lecture Notes in Computer Science  
In 2016, the 14th edition of ImageCLEF, three main tasks were proposed: 1) identification, multi-label classification and separation of compound figures from biomedical literature; 2) automatic annotation  ...  ImageCLEF is an ongoing initiative that promotes the evaluation of technologies for annotation, indexing and retrieval for providing information access to collections of images in various usage scenarios  ...  Acknowledgements The general coordination and the handwritten retrieval task have been supported  ... 
doi:10.1007/978-3-319-44564-9_25 fatcat:smnjpwfcnjee3h52lbhau75j4e

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  
Furthermore, the medical annotation task, that traditionally has been under the ImageCLEF umbrella and that this year celebrates its tenth anniversary, has been organized in conjunction with AMIA for the  ...  Since its first edition in 2003, ImageCLEF has become one of the key initiatives promoting the benchmark evaluation of algorithms for the cross-language annotation and retrieval of images in various domains  ...  Participation and Results In total over 60 groups registered for the medical tasks and obtained access to the data sets.10 of the registered groups submitted results to the medical tasks with a total of  ... 
doi:10.1007/978-3-642-40802-1_26 fatcat:wi5nqtvoxbch3jtl2u7qzwo5fm

The CLEF 2005 Cross–Language Image Retrieval Track [chapter]

Paul Clough, Henning Müller, Thomas Deselaers, Michael Grubinger, Thomas M. Lehmann, Jeffery Jensen, William Hersh
2006 Lecture Notes in Computer Science  
Four tasks were offered in the ImageCLEF track: a ad-hoc retrieval from an historic photographic collection, ad-hoc retrieval from a medical collection, an automatic image annotation task, and a user-centered  ...  In this paper we describe the ImageCLEF tasks, submissions from participating groups and summarise the main findings.  ...  The establishment of the IRMA database was funded by the German Research Community DFG under grand Le 1108/4.  ... 
doi:10.1007/11878773_60 fatcat:tnktsl6hkbbupofowyjau6t3g4

Overview of the ImageCLEFmed 2006 Medical Retrieval and Medical Annotation Tasks [chapter]

Henning Müller, Thomas Deselaers, Thomas Deserno, Paul Clough, Eugene Kim, William Hersh
2007 Lecture Notes in Computer Science  
This paper describes the medical image retrieval and annotation tasks of ImageCLEF 2006. Both tasks are described with respect to goals, databases, topics, results, and techniques.  ...  The best system of 2005 would have received a position in the middle in 2006. keywords: image retrieval, automatic image annotation, medical information retrieval  ...  /1, the American National Science Foundation (NSF) with grant ITR-0325160, and the EU 6th Framework Program with the SemanticMining (IST NoE 507505) and MUSCLE NoE.  ... 
doi:10.1007/978-3-540-74999-8_72 fatcat:cdsdiajxufhw7fwg4uelxv524a

Combining Global Features within a Nearest Neighbor Classifier for Content-based Retrieval of Medical Images

Mark Oliver Güld, Christian Thies, Benedikt Fischer, Thomas Martin Lehmann
2006 Conference and Labs of the Evaluation Forum  
For the medical automatic annotation task, a categorization rate of 78.6% is obtained, which ranks 12th among 28 submissions.  ...  When applied in the medical retrieval task, this combination of classifiers yields a mean average precision (MAP) of 0.0172, which is rank 11 of 11 submitted runs for automatic, visual only systems.  ...  Discussion The weighing coefficients used for the medical automatic annotation task of ImageCLEF 2005 are also suitable for the 2006 task.  ... 
dblp:conf/clef/GuldTFL06 fatcat:k5ykwr4odvcnrdzxgmjdx7imi4
« Previous Showing results 1 — 15 out of 78 results