present a general fusion framework (GFF) aimed towards a combined knowledge representation predicting disease recurrence. To the best of our knowledge, GFF represents the first formal attempt to fuse biomedical image and non-image information directly at the data level as opposed to the decision level

in the video sequences. From a data-collection point of view, tracking is vital because it adds non-frontal poses to our face collection. This is important because we know of no other method for collecting images of non-frontal faces “in the wild”. 1.

for Medicine) standard1 is a non-proprietary data interchange protocol, digital image format, and file structure for image and image-related information. It is typically used in radiology, cardiology, and similar imaging-intensive departments. DICOM is used in these contexts to integrate

’ speech signal are given as input vectors to train the speaker specific SVM’s. In this work, we propose a new feature representation based on GMM to construct the input vectors to train the SVM to discriminate the true-target speaker access class from the non-target speaker access class. The results

Despite of an increasing use of Confocal Laser Endomicroscopy (CLE) in gastroen-terology, an objective interpretation of this data is not established and its processing still states a very difficult task due to the high amount of noise and motion blur shown in these images. Nevertheless

) for data representation and integration and a Probabilistic Boosting Tree classifier for data classification. SE provides an alternate representation of the data by non-linearly transforming high dimensional data into a low dimensional embedding space such that the relative adjacencies between objects

While the plethora of information from multiple imaging and non-imaging data streams presents an opportunity for discovery of fused multimodal, multiscale biomarkers, they also introduce multiple independent sources of noise that hinder their collective utility. The goal of this work is to create

Abstract. Increasing use is being made of contrast-enhanced Magnetic Resonance Imaging (Gd-DTPA) for breast cancer assessment since it provides 3D functional information via pharmacokinetic interaction between contrast agent and tumour vascularity, and because it is applicable to women of all ages

Abstract—In this study we present an efficient image categorization and retrieval system applied to medical image databases, in particular large radiograph archives. The methodology is based on local patch representation of the image content, using a “bag of visual words ” approach. We explore

Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university education on the internet, free of charge, a real possibility. At this pivotal moment it is appropriate to explore the potential for obtaining comprehensive bioinformatics training with currently existing free video resources. This article pre-sents such a bioinformatics curric-ulum in the form of a virtual course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field. Online Learning Comes of Age Online academic ‘‘courseware’ ’ at the university level has now been available to the public for a decade, the earliest concerted effort having originated in 2002 with the Massachusetts Institute of Technology (MIT) and their OpenCour-seWare initiative