Medical image retrieval to search for clinically relevant and visually similar images depicting suspecious lesions have been attracting research interest. Content-based image retrieval (CBIR) is an important alternate and complement to traditional text-based retrieval using keywords. We have implemented CBIR system based on effective use of texture information within the images obtained by stat...

Visual information retrieval is an emerging domain in the medical field as it has been in computer vision for more than ten years. It has the potential to help better managing the rising amount of visual medical data. One of the most frequent application fields for content– based medical image retrieval (CBIR) is diagnostic aid. By submitting an image showing a certain pathology to a CBIR syste...

Medical image retrieval to search for clinically relevant and visually similar images depicting suspecious lesions have been attracting research interest. Content-based image retrieval (CBIR) is an important alternate and complement to traditional text-based retrieval using keywords. We have implemented CBIR system based on effective use of texture information within the images obtained by stat...

This paper describes the results after using an automatic classification method to help improve the retrieval of medical images. Using a large dataset of medical images, we established links between low-level features from medical images and high-level features from textual codes of Image Retrieval for Medical Application (IRMA). This paper also explains the process and methods used to automati...

Content Based Image Retrieval (CBIR) is an important research area in the field of multimedia information retrieval. The application of CBIR in the medical domain has been attempted before, however the use of CBIR in medical diagnostics is a daunting task. The goal of diagnostic medical image retrieval is to provide diagnostic support by displaying relevant past cases, along with proven patholo...

in this paper we propose novel algorithms for retrieving dental images from databases by their contents. based on special information of dental images, for better content based dental image retrieval and representation, the image attributes are used. we propose disr (dental image segmentation and retrieval), a content-based image retrieval method which is robust to translation and scaling of th...

image retrieval is an important research field which has received great attention in the last decades. in this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. for text-based features, keywords and for content-based features, color and texture features have been used. query in this system contains some keywords and an input...

In order to improve the efficiency of massive medical images retrieval, against the defects of the single-node medical image retrieval system, a massive medical images retrieval system based on Hadoop is put forward. Brushlet transform and Local binary patterns algorithm are introduced firstly to extract characteristics of the medical example image, and store the image feature library in the HD...