Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accu...

Bimodal imaging combines two imaging modalities in order to benefit from their advantages and compensate the limitations of each modality. This technique could accurately detect diseases for diagnostic purposes. Nanoparticles simultaneously offer diagnostic data via various imaging modalities owing to their unique properties. Moreover, bimodal nanoprobes could be incorporated into theranostic s...

it has been demonstrated that anxiety is accompanied by significant warm up in the periorbital area. this warm up was attributed to the increased blood circulation in the area around the eyes. the whole pattern makes physiological and evolutionary sense since it represents a mechanism to facilitate rapid eye movements during preparedness for fight. this increased blood flow dissipates convectiv...

agent technology is an emerging and promising research area in software technology, which increasingly contributes to the development of value-added information systems for large healthcare organizations due to its capability to automatically modify themselves in response to changes in their operating environment. multi agent system (mas) approach is the construction of a complex system as a se...

In this work, a first-of-its-kind fully integrated tri-modality system that combines fluorescence, diffuse optical and x-ray tomography (FT/DOT/XCT) into the same setting is presented. The purpose of this system is to perform quantitative fluorescence tomography using multi-modality imaging approach. XCT anatomical information is used as structural priori while optical background heterogeneity ...

We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using multi-modal image data, to facilitate early identification of AD related pathologies. Several recent papers have demonstrated that such classification is possible with MR or PET images, using machine learning methods such as SVM and boosting. These algorithms learn the classifier...