ASSERT: a physician-in-the-loop content-based retrieval system for HRCT image databases
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Evaluating bag-of-visual-words representations in scene classification
Proceedings of the international workshop on Workshop on multimedia information retrieval
Lung Tissue Classification in HRCT Data Integrating the Clinical Context
CBMS '08 Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems
Diffuse parenchymal lung diseases: 3D automated detection in MDCT
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
A texton-based approach for the classification of lung parenchyma in CT images
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Reduction of breast biopsies with a modified self-organizing map
IEEE Transactions on Neural Networks
Overview of the second workshop on medical content---based retrieval for clinical decision support
MCBR-CDS'11 Proceedings of the Second MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Retrieval of 4d dual energy CT for pulmonary embolism diagnosis
MCBR-CDS'12 Proceedings of the Third MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Proceedings of the 1st ACM international workshop on Multimedia indexing and information retrieval for healthcare
Retrieval of high-dimensional visual data: current state, trends and challenges ahead
Multimedia Tools and Applications
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Interstitial lung diseases (ILDs) are regrouping over 150 heterogeneous disorders of the lung parenchyma. High---Resolution Computed Tomography (HRCT) plays an important role in diagnosis, as standard chest x---rays are often non---specific for ILDs. Assessment of ILDs is considerd hard for clinicians because the diseases are rare, patterns often look visually similar and various clinical data need to be integrated. An image retrieval system to support interpretation of HRCT images by retrieving similar images is presented in this paper. The system uses a wavelet transform based on Difference of Gaussians (DoG) in order to extract texture descriptors from a set of 90 image series containing 1679 manually annotated regions corresponding to various ILDs. Visual words are used for feature aggregation and to describe tissue patterns. The optimal scale---progression scheme, number of visual words, as well as distance measure for clustering to generate visual words are investigated. A sufficiently high number of visual words is required to accurately describe patterns with high intra---class variations such as healthy tissue. Scale progression has less influence and the Euclidean distance performs better than other distances. The results show that the system is able to learn the wide intra---class variations of healthy tissue and the characteristics of abnormal lung tissue to provide reliable assistance to clinicians.