An experimental comparison of a large number of different image descriptors for content-based image retrieval is presented. Many of the papers describing new techniques and descri...
The demand for automatically annotating and retrieving medical images is growing faster than ever. In this paper, we present a novel medical image retrieval method based on SEMIsu...
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. A total of 15 g...
This article describes the technologies used for the various runs submitted by the University of Geneva in the context of the 2004 ImageCLEF competition. As our expertise is mainly...
Content–based image retrieval in the medical domain is an extremely hot topic in medical imaging as it promises to help better managing the large amount of medical images being ...
This paper proposes a content-based medical image retrieval (CBMIR) framework using dynamically optimized features from multiple regions of medical images. These regional features...
Wei Xiong, Bo Qiu, Qi Tian, Changsheng Xu, Sim Hen...
Relevance feedback (RF) has been an active research area in Content-based Image Retrieval (CBIR). RF intends to bridge the gap between the low-level image features and the high-le...
Xiaoqian Xu, D. J. Lee, Sameer Antani, L. Rodney L...
The demand for automatically annotating and retrieving medical images is growing faster than ever. In this paper, we present a novel medical image retrieval method based on SEMIsu...
In this paper, we present a knowledge-assisted approach to index and retrieve large volume of medical images. Both images and associated texts are indexed using medical concepts f...