A Pattern Similarity Scheme for Medical Image Retrieval

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...

A Hierarchical Characterization Scheme for Image Retrieval

In this paper, we present a study of hierarchically characterizing image content from coarse level to fine level conducted using a series of shape features as a case in point. In this work, we have empirically proved that this hierarchical characterization is effective and necessary. We have used this hierarchical multimedia content characterization scheme in our shape retrieval experiments and...

Image Fusion For Medical Image Retrieval

Learning Similarity for Texture Image Retrieval

A novel algorithm is proposed to learn pattern similarities for texture image retrieval. Similar patterns in di erent texture classes are grouped into a cluster in the feature space. Each cluster is isolated from others by an enclosed boundary, which is represented by several support vectors and their weights obtained from a statistical learning algorithm called support vector machine (SVM). Th...

A Comparative Study of Similarity Measures for Content-Based Medical Image Retrieval

This note summarizes methodologies employed in our submissions for the medical retrieval subtask of 2012 ImageCLEF competition. Our work aims to provide a systematic comparison of various similarity measures in the Medical CBIR application context. Our system consists of the standard bag-of-words features with SIFT. Computed features are then compared by using various plug-in similarity measure...