Content based radiology image retrieval using a fuzzy rule based scalable composite descriptor
The rapid advances made in the field of radiology, the increased frequency in which oncological diseases appear, as well as the demand for regular medical checks, led to the creation of a large database of radiology images in every hospital or medical center. There is now an imperative need to create an effective method for the indexing and retrieval of these images. This paper proposes a new method of content based radiology medical image retrieval. The description of images relies on a Fuzzy Rule Based Compact Composite Descriptor (CCD), which includes global image features capturing both brightness and texture characteristics in a 1D Histogram. Furthermore, the proposed descriptor includes the spatial distribution of the information it describes. The most important feature of the proposed descriptor is that its size adapts according to the storage capabilities of the application that uses it. Experiments carried out on a large group of images show that even at 48 bytes per image, the proposed descriptor demonstrates a high level of accuracy in its results. To evaluate the performance of the proposed feature, the mean average precision was used.
image retrieval medical images cbmir fuzzy methods