Predicting Clinical Image Delivery Time by Monitoring PACS Queue Behavior

Single Image Action Recognition by Predicting Space-Time Saliency

We propose a novel approach based on deep Convolutional Neural Networks (CNN) to recognize human actions in still images by predicting the future motion, and detecting the shape and location of the salient parts of the image. We make the following major contributions to this important area of research: (i) We use the predicted future motion in the static image (Walker et al., 2015) as a means o...

Discrete Tomographic and PACS Image Processing Systems

Monitoring of Tectonic Deformation by Mining Satellite Image Time Series

In this paper, an original approach for analyzing Interferometric Synthetic Aperture Radar (InSAR) time series is presented and applied to the monitoring of creep along a major active fault. InSAR data are computed from satellite acquisitions and allow ground deformations occurring between different dates to be measured with high precision over large areas. However, measurement precision remain...

Content-Based Image Retrieval in PACS

In this paper, we propose the concept of content-based image retrieval (CBIR) and demonstrate its potential use in picture archival and communication system (PACS). We address the importance of image retrieval in PACS and highlight the drawbacks existing in traditional textual-based retrieval. We use a digital mammogram database as our testing data to illustrate the idea of CBIR, where retrieva...

Performance Contracts: Predicting and Monitoring Grid Application Behavior

The Internet and the growing availability of inexpensive yet powerful commodity hardware has changed our view of computing. Computational grids have emerged as a new paradigm for high-performance computing. Grids consist of geographically distributed computational resources, such as supercomputers, clusters of workstations, scientific instruments, storage systems, visualization systems and so o...