Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition

A Radon-based Convolutional Neural Network for Medical Image Retrieval

Image classification and retrieval systems have gained more attention because of easier access to high-tech medical imaging. However, the lack of availability of large-scaled balanced labelled data in medicine is still a challenge. Simplicity, practicality, efficiency, and effectiveness are the main targets in medical domain. To achieve these goals, Radon transformation, which is a well-known t...

Image Fusion For Medical Image Retrieval

Report on the CLEF Experiment: Combining Image and Multilingual Search for Medical Image Retrieval

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 in the field of medical image retrieval, we will concentrate most of our effort on the medical image retrieval task. Described are the runs that were submitted by our group including technical details for each of the...

Image-Text Dataset Generation for Image Annotation and Retrieval

This paper presents a new dataset of images gathered from the Web with corresponding text obtained from the webpages near where the images appeared. Already extracted features are provided to ease the dataset usage for other researchers. An initial release of 250,000 images is targeted at automatic image annotation with unsupervised data. This dataset is the one being used for the ImageCLEF 201...

MinMax Radon Barcodes for Medical Image Retrieval

Content-based medical image retrieval can support diagnostic decisions by clinical experts. Examining similar images may provide clues to the expert to remove uncertainties in his/her final diagnosis. Beyond conventional feature descriptors, binary features in different ways have been recently proposed to encode the image content. A recent proposal is “Radon barcodes” that employ binarized Rado...