Text corpora are structured sets of text segments that can be annotated or interrelated. Expanding on this, we can define a database of images as an iconographic multimodal corpus with annotated images and the relations between images as well as between images and texts. The Goethe-Museum in Frankfurt holds a significant collection of art work and texts relating to Goethe’s Faust from the early...

Remote Sensing Images (RSIs) have been used as a major source of data, particularly with respect to the creation of thematic maps. This process is usually modeled as a supervised classification problem where the system needs to learn the patterns of interest provided by the user and assign a class to the rest of the image regions. Associated with the nature of RSIs, there are several challenges...

Reading is a hobby to open the knowledge windows. Besides, it can provide the inspiration and spirit to face this life. By this way, concomitant with the technology development, many companies serve the e-book or book in soft file. The system of this book of course will be much easier. No worry to forget bringing the multimodal location estimation of videos and images book. You can open the dev...

Molecular imaging is rapidly developing as a powerful tool in research and medical diagnostic. By integrating complementary signal reporters into a single nanoparticulate contrast agent, multimodal molecular imaging can be performed as scalable images with high sensitivity, resolution and specificity. In this review, multifunctional nanoparticles (MFNPs) are classified into four types: conjugat...

In the medical domain, misdiagnoses and diagnostic uncertainty put lives at risk and incur substantial financial costs. Clearly, medical reasoning and decision-making need to be better understood. We explore a possible link between linguistic expression and diagnostic correctness. We report on an unusual data set of spoken diagnostic narratives used to computationally model and predict diagnost...

Description: A novel method is developed for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape contexts is used to find th...

OBJECTIVE To demonstrate the possibilities, advantages and limitations of virtual bronchoscopy using data sets from positron emission tomography (PET) and computed tomography (CT). MATERIALS AND METHODS Eight consecutive patients with non-small cell lung cancer (NSCLC) underwent PET/CT. PET was performed with a glucose analog, 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (18F-FDG), using a state-...

In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel sentence descriptions to explain the content of images. It directly models the probability distribution of generating a word given previous words and the image. Image descriptions are generated by sampling from this distribution. The model consists of two sub-networks: a deep recurrent neural netw...

Description: A novel method is developed for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape contexts is used to find th...

Description: A novel method is developed for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape contexts is used to find th...