Journal ArticleDOI
Automatic medical image annotation in ImageCLEF 2007: Overview, results, and discussion
TLDR
The results show that methods which build on local image descriptors and discriminative models are able to provide good predictions of the image classes, mostly by using techniques that were originally developed in the machine learning and computer vision domain for object recognition in non-medical images.About:
This article is published in Pattern Recognition Letters.The article was published on 2008-11-01. It has received 59 citations till now. The article focuses on the topics: Automatic image annotation & Image retrieval.read more
Citations
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Journal ArticleDOI
Discriminative cue integration for medical image annotation
TL;DR: A multi-cue approach to automatic medical image annotation is proposed, which represents images using global and local features and combines three alternative approaches, all based on the support vector machine algorithm.
Book ChapterDOI
Overview of the CLEF 2009 medical image annotation track
TL;DR: The aim is to understand how each strategy answers to the increasing number of classes and to the unbalancing in the medical image annotation task in ImageCLEF 2009.
Proceedings ArticleDOI
Creating a classification of image types in the medical literature for visual categorization
TL;DR: A hierarchy for classification of biomedical illustrations with the goal of using it for visual classification and thus as a basis for retrieval and to have a terminology for visual image classification based on image types distinguishable by visual means and occurring in the medical open access literature.
Journal ArticleDOI
Robust Learning-Based Parsing and Annotation of Medical Radiographs
TL;DR: The algorithm was used to enhance advanced image visualization workflows by enabling content-sensitive hanging-protocols and auto-invocation of a computer aided detection algorithm for identified PA-AP chest images and could be utilized for several image parsing applications including anatomy/organ region of interest prediction and optimized image visualization.
Journal ArticleDOI
Adapting content-based image retrieval techniques for the semantic annotation of medical images
Ashnil Kumar,Shane Dyer,Jinman Kim,Changyang Li,Philip H. W. Leong,Michael J. Fulham,Dagan Feng,Dagan Feng +7 more
TL;DR: This paper presents a method for the automatic semantic annotation of medical images that leverages techniques from content-based image retrieval (CBIR), a well-established image search technology that uses quantifiable low-level image features to represent the high-level semantic content depicted in those images.
References
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The PASCAL visual object classes challenge 2006 (VOC2006) results
TL;DR: This report presents the results of the 2006 PASCAL Visual Object Classes Challenge (VOC2006).
Journal ArticleDOI
Efficient and effective querying by image content
Christos Faloutsos,R. Barber,Myron D. Flickner,James Lee Hafner,W. Niblack,Dragutin Petkovic,W. Equitz +6 more
TL;DR: A set of novel features and similarity measures allowing query by image content, together with the QBIC system, and a new theorem that makes efficient filtering possible by bounding the non-Euclidean, full cross-term quadratic distance expression with a simple Euclidean distance.
Journal ArticleDOI
Information extraction
Jim Cowie,Wendy G. Lehnert +1 more
TL;DR: A relatively new development—information extraction (IE)—is the subject of this article and can transform the raw material, refining and reducing it to a germ of the original text.
Proceedings ArticleDOI
The challenge problem for automated detection of 101 semantic concepts in multimedia
Cees G. M. Snoek,Marcel Worring,Jan C. van Gemert,Jan-Mark Geusebroek,Arnold W. M. Smeulders +4 more
TL;DR: The challenge problem for generic video indexing is introduced to gain insight in intermediate steps that affect performance of multimedia analysis methods, while at the same time fostering repeatability of experiments.