نتایج جستجو برای: multiparametric mri

تعداد نتایج: 108152  

2015
Ralf S. Eschbach Wolfgang P. Fendler Philipp M. Kazmierczak Marcus Hacker Axel Rominger Janette Carlsen Heidrun Hirner-Eppeneder Jessica Schuster Matthias Moser Lukas Havla Moritz J. Schneider Michael Ingrisch Lukas Spaeth Maximilian F. Reiser Konstantin Nikolaou Clemens C. Cyran

OBJECTIVES To investigate a multimodal, multiparametric perfusion MRI / 18F-fluoro-deoxyglucose-(18F-FDG)-PET imaging protocol for monitoring regorafenib therapy effects on experimental colorectal adenocarcinomas in rats with immunohistochemical validation. MATERIALS AND METHODS Human colorectal adenocarcinoma xenografts (HT-29) were implanted subcutaneously in n = 17 (n = 10 therapy group; n...

Journal: :Nature Reviews Clinical Oncology 2014

Journal: :American Journal of Physiology-Renal Physiology 2018

Journal: :Journal of the Belgian Society of Radiology 2018

2008
Zhiqiang Lao Dinggang Shen Dengfeng Liu Abbas F. Jawad Elias R. Melhem Lenore J. Launer R. Nick Bryan Christos Davatzikos

Materials and Methods. In this article, we present a computer-assisted WML segmentation method, based on local f tures extracted from multiparametric magnetic resonance imaging (MRI) sequences (ie, T1-weighted, T2-weighted, pro density-weighted, and fluid attenuation inversion recovery MRI scans). A support vector machine classifier is first tr on expert-defined WMLs, and is then used to classi...

Journal: :Diagnostic and interventional radiology 2014
Felix Nensa Karsten Beiderwellen Philipp Heusch Axel Wetter

Fully integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) scanners have been available for a few years. Since then, the number of scanner installations and published studies have been growing. While feasibility of integrated PET/MRI has been demonstrated for many clinical and preclinical imaging applications, now those applications where PET/MRI provides a clear benef...

2013

In this study, a multiparametric magnetic resonance image (MRI) based technique of detecting prostate cancer is developed. A machine learning algorithm, based on random forest is used to classify the normal and cancer regions. Three features extracted from dynamic contrast enhanced MRI and two features extracted from diffusion tensor MRI is used to train the classifier. The classifier is traine...

2015
Christian Weis Andreas Hess Lubos Budinsky Ben Fabry Alexander Annala

The migration of cells within a living organism can be observed with magnetic resonance imaging (MRI) in combination with iron oxide nanoparticles as an intracellular contrast agent. This method, however, suffers from low sensitivity and specificty. Here, we developed a quantitative non-invasive in-vivo cell localization method using contrast enhanced multiparametric MRI and support vector mach...

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