Results 1 to 10 of about 2,219,909 (313)

Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space [PDF]

Frontiers in Neuroinformatics, 2018
Diffusion MRI requires sufficient coverage of the diffusion wavevector space, also known as the q-space, to adequately capture the pattern of water diffusion in various directions and scales.
Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen, Dinggang Shen, Pew-Thian Yap   +6 more
doaj   +5 more sources

Evaluating fibre orientation dispersion in white matter: Comparison of diffusion MRI, histology and polarized light imaging

NeuroImage, 2017
Diffusion MRI is an exquisitely sensitive probe of tissue microstructure, and is currently the only non-invasive measure of the brain's fibre architecture.
Jeroen Mollink, Michiel Kleinnijenhuis, Anne-Marie van Cappellen van Walsum, Stamatios N. Sotiropoulos, Michiel Cottaar, Christopher Mirfin, Mattias P. Heinrich, Mark Jenkinson, Menuka Pallebage-Gamarallage, Olaf Ansorge, Saad Jbabdi, Karla L. Miller   +11 more
doaj   +2 more sources

Prostate carcinoma: Accuracy of diagnosis and differentiation with Dynamic Contrast-Enhanced MRI and Diffusion Weighted Imaging

The Egyptian Journal of Radiology and Nuclear Medicine, 2015
Background: Diffusion weighted image (DWI) and dynamic contrast enhanced MR imaging (DCE-MRI) provide excellent parameters that are useful for differentiating cancer from normal tissue in prostatic cancer patients. Purpose: To define the diagnostic value
Sayed Zidan, Hazim I. Tantawy
doaj   +2 more sources

Probing white-matter microstructure with higher-order diffusion tensors and susceptibility tensor MRI [PDF]

Frontiers in Integrative Neuroscience, 2013
Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging has provided another unique tool for assessing the ...
Chunlei eLiu, Chunlei eLiu, Nicole eMurphy, Wei eLi   +3 more
doaj   +3 more sources

Machine learning diagnosis of mild cognitive impairment using advanced diffusion MRI and CSF biomarkers [PDF]

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
INTRODUCTION Machine learning applied to neuroimaging can help with medical diagnosis and early detection by identifying biomarkers of subtle changes in brain structure and function.
Alexander Y. Guo, John P. Laporte, Kavita Singh, Jonghyun Bae, Keagan Bergeron, Angelique deRouen, Noam Y. Fox, Nathan Zhang, Isabel Carino‐Bazan, Mary E. Faulkner, Rafael deCabo, Dan Benjamini, Zhaoyuan Gong, Mustapha Bouhrara, for the Alzheimer's Disease Neuroimaging Initiative   +14 more
doaj   +2 more sources

Susceptibility and diffusion MRI biomarkers predict development of Parkinsonism in iRBD. [PDF]

NPJ Parkinsons Dis
Varga Z, Nepozitek J, Hlavnicka J, Keller J, Ojha A, Pantano P, Marecek S, Sonka K, Dusek P.   +8 more
europepmc   +3 more sources

In vivo submillimeter diffusion MRI dataset of 9 macaque brains curated for tractography [PDF]

Scientific Data
In vivo diffusion magnetic resonance imaging (MRI) is critical to access detailed information about the brain microstructure and connectivity. In non-human primates (NHPs), especially macaque monkeys, such acquisitions should be carried out at a ...
Alex Valcourt Caron, Nadège Corbin, Adrien Boissenin, Ankur Gupta, Tho-Hai Nguyen, Serge Anandra, Sylvain Miraux, Maxime Descoteaux, Laurent Petit, Fabien B. Wagner   +9 more
doaj   +2 more sources

Data on the verification and validation of segmentation and registration methods for diffusion MRI

Data in Brief, 2016
The verification and validation of segmentation and registration methods is a necessary assessment in the development of new processing methods. However, verification and validation of diffusion MRI (dMRI) processing methods is challenging for the lack ...
Oscar Esteban, Dominique Zosso, Alessandro Daducci, Meritxell Bach-Cuadra, María J. Ledesma-Carbayo, Jean-Philippe Thiran, Andres Santos   +6 more
doaj   +2 more sources

DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models [PDF]

International Conference on Learning Representations, 2023
Magnetic resonance imaging (MRI) is a common and life-saving medical imaging technique. However, acquiring high signal-to-noise ratio MRI scans requires long scan times, resulting in increased costs and patient discomfort, and decreased throughput. Thus,
Tiange Xiang, Mahmut Yurt, Ali B. Syed, K. Setsompop, A. Chaudhari   +4 more
semanticscholar   +1 more source

Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model [PDF]

Medical Physics (Lancaster), 2023
BACKGROUND AND PURPOSE Magnetic resonance imaging (MRI)-based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for CT simulation and error-prone image registration, ultimately reducing patient ...
Shaoyan Pan, E. Abouei, J. Wynne, Tonghe Wang, Richard L. J. Qiu, Yuheng Li, Chih-Wei Chang, Junbo Peng, J. Roper, P. Patel, David S. Yu, H. Mao, Xiaofeng Yang   +12 more
semanticscholar   +1 more source