Introduction: Content Based Image Retrieval (CBIR) is a method of image searching and retrieval in a  database. In medical applications, CBIR is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. As the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retri...

When dealing with the complexity of an image as part of the indexing process, keywords are not sufficient to obtain an index that is a faithful representation of the image content. We propose to use the conceptual graphs formalism as the indexing language, which allows to use not only keywords, but also relations between them. The obtained indexes are more precise, and retrieval effectiveness i...

This paper presents our participation in medical image retrieval task of ImageCLEF 2012. Our aim is to study the effectiveness of using conceptual indexing comparing to word indexing in medical image retrieval. For this aim, we have used in the one hand the Terrier tool for textual indexing and for textual retrieval, and on another hand, the MetaMap tool for conceptual indexing and Vector model...

Image indexing based on Modified Color Co-occurrence Matrix (MCCM) is proposed in this paper. First, CCM is simplified to represent the number of color (hue) pairs between adjacent pixels in the image. And then, CCM is split into diagonal and non-diagonal elements that constitute two elements of MCCM. Indexing the image by MCCM could exploit shape information in abstract level. Proposed MCCM is...

In this paper we present a new approach to image indexing and retrieval based on image correlogram. We show that in comparison with usually used approaches, i.e. image histogram and autocorrelogram, image correlogram gives significantly better results in image retrieval. These results are achievable without increasing computational cost in image indexing or retrieval. In the experimental part o...

This paper summarizes our work and our understanding on volumetric pathological neuroimage retrieval under the framework of classification-driven feature selection. The main effort concerns off-line image feature space reduction for improved image indexing feature discriminating power as well as reduced computational cost during on-line pathological neuroimage retrieval. Keywrods: 3D image, fea...

This paper proposes a new image representation scheme for database indexing. The application domain is \image-based" indexing as opposed to \content-based" indexing. In other words, given a database of images and associated data, we want to search the database for a known image so as to retrieve the data associated with the image. A concrete example is to search a database of aerial images so a...