نتایج جستجو برای: biomedical mri

تعداد نتایج: 165212  

2005
E. Heijman W. de Graaf C. Diekmann A. Nauerth G. Strijkers K. Nicolay

E. Heijman, W. de Graaf, C. Diekmann, A. Nauerth, G. Strijkers, K. Nicolay Biomedical NMR, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands, Bruker BioSpin MRI GmbH, Ettlingen, Germany Introduction In cardiac research in vivo studies of mice are indispensable to gain an improved understanding of cardiovascular disease mechanisms and to develop nov...

2016
Wei Li Jan Zaloga Yaping Ding Yufang Liu Christina Janko Monika Pischetsrieder Christoph Alexiou Aldo R. Boccaccini

The promising potential of magnetic polymer microspheres in various biomedical applications has been frequently reported. However, the surface hydrophilicity of superparamagnetic iron oxide nanoparticles (SPIONs) usually leads to poor or even failed encapsulation of SPIONs in hydrophobic polymer microspheres using the emulsion method. In this study, the stability of SPIONs in poly(3-hydroxybuty...

Journal: :Nature nanotechnology 2015
Stephen J DeVience Linh M Pham Igor Lovchinsky Alexander O Sushkov Nir Bar-Gill Chinmay Belthangady Francesco Casola Madeleine Corbett Huiliang Zhang Mikhail Lukin Hongkun Park Amir Yacoby Ronald L Walsworth

Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI) provide non-invasive information about multiple nuclear species in bulk matter, with wide-ranging applications from basic physics and chemistry to biomedical imaging. However, the spatial resolution of conventional NMR and MRI is limited to several micrometres even at large magnetic fields (>1 T), which is inadeq...

Journal: :American journal of nuclear medicine and molecular imaging 2012
Donald D Nolting Michael L Nickels Ning Guo Wellington Pham

Molecular imaging is an attractive modality that has been widely employed in many aspects of biomedical research; especially those aimed at the early detection of diseases such as cancer, inflammation and neurodegenerative disorders. The field emerged in response to a new research paradigm in healthcare that seeks to integrate detection capabilities for the prediction and prevention of diseases...

2014
Eduardo Caverzasi Maria Luisa Mandelli Stephen J. DeArmond Christopher P. Hess Paolo Vitali Nico Papinutto Abby Oehler Bruce L. Miller Irina V. Lobach Stefano Bastianello Michael D. Geschwind Roland G. Henry

1 Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA 2 Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA 94143, USA 3 Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA 4 Institute for Neurodegenerative Diseases, University of California San Francisco, San Francisco,...

2014
Amin Azizi Brian S. Mitchell Noshir S. Pesika

Among various magnetic nanoparticles that have been studied for potential biomedical applications, FeCo nanoparticles are promising candidates because of their high saturation magnetization and high Curie temperature. [ 3–5 ] However, the ease of oxidation, dissolution in acidic environments, and potential toxicity of these materials in their native state restrict their use in biomedical applic...

Journal: :caspian journal of internal medicine 0
mehrdad saravi ahmad tamadoni rozita jalalian hasan mahmoodi nesheli mosatafa hojati saeed ramezani

background: iron-mediated cardiomyopathy is the main complication of thalassemia major (tm) patients. therefore, there is an important clinical need in the early diagnosis and risk stratification of patients. the aim of this study was to evaluate the efficacy of tissue doppler imaging (tdi) to study cardiac iron overload in patients with tm using t2* magnetic resonance (mr) as the gold-standard...

2011
Aruna Devi

In this paper, a survey has been made on the applications of intelligent computing techniques for diagnostic sciences in biomedical image classification. Several state-of-the-art Artificial Intelligence (AI) techniques for automation of biomedical image classification are investigated. This study gathers representative works that exhibit how AI is applied to the solution of very different probl...

Journal: :Biomedical Signal Processing and Control 2023

Although existing deep learning compressed-sensing-based Magnetic Resonance Imaging (CS-MRI) methods have achieved considerably impressive performance, explainability and generalizability continue to be challenging for such since the transition from mathematical analysis network design not always natural enough, often most of them are flexible enough handle multi-sampling-ratio reconstruction a...

Journal: :IEEE Access 2022

Convolutional neural networks (CNNs) have become the de facto algorithms of choice for semantic segmentation tasks in biomedical image processing. Yet, models based on CNNs remain susceptible to domain shift problem, where a mismatch between source and target distributions could lead drop performance. were recently shown exhibit textural bias when processing natural images, recent studies sugge...

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