Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Modeling and Classifying Breast Tissue Density in Mammograms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Introduction to Information Retrieval
Introduction to Information Retrieval
Discriminative cue integration for medical image annotation
Pattern Recognition Letters
Lire: lucene image retrieval: an extensible java CBIR library
MM '08 Proceedings of the 16th ACM international conference on Multimedia
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
An SVM confidence-based approach to medical image annotation
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Sparse patch-histograms for object classification in cluttered images
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Introducing space and time in local feature-based endomicroscopic image retrieval
MCBR-CDS'09 Proceedings of the First MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Texture edge statistics for efficient retrieval of biomedical images
Proceedings of the 5th ACM COMPUTE Conference: Intelligent & scalable system technologies
Hi-index | 0.00 |
Image classification methods based on text utilize terms extracted from image annotations (image caption, image-related article, etc.) to achieve classification. For images involving different anatomical structures (chest, spine, etc.), however, the precision of pure textual classification often suffers from highly complex text contents (e.g. text terms extracted out of two MR abdomen images may be quite different from each other: terms from one image may concerns gastroenteritis while the other contains terms involving hysteromyoma). This paper tackles the anatomy image classification problem using a hybrid approach. First, a mutual information (MI) based filter is applied to select a set of terms with top MI scores for each anatomical class and help reduce the noise existing in the raw text. Second, local features extracted from the images are transformed as visual descriptors. Last, a hybrid scheme on the results from the textual and visual methods is applied to achieved further improvement of the classification results. Experiments show that this hybrid scheme improves the results over the sole textual or visual method on different anatomical class settings.