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Author:
Publisher:
ISBN: 9789461825421
Category :
Languages : en
Pages : 235
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Book Description
Author:
Publisher:
ISBN: 9789461825421
Category :
Languages : en
Pages : 235
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Book Description
Author: Michael Chappell
Publisher: Oxford University Press
ISBN: 0198793812
Category : Medical
Languages : en
Pages : 157
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Book Description
ASL is an increasingly popular tool to study the brain. The aim of this primer is to equip someone new to the field with the knowledge to make informed choices about ASL acquisition and analysis. While providing a stand-alone introduction to this subject, the text can be read with others in the series for a comprehensive overview of neuroimaging.
Author: Richard B. Buxton
Publisher: Cambridge University Press
ISBN: 0521899958
Category : Medical
Languages : en
Pages : 479
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Book Description
This is the second edition of a useful introductory book on a technique that has revolutionized neuroscience, specifically cognitive neuroscience. Functional magnetic resonance imaging (fMRI) has now become the standard tool for studying the brain systems involved in cognitive and emotional processing. It has also been a major factor in the consilience of the fields of neurobiology, cognitive psychology, social psychology, radiology, physics, mathematics, engineering, and even philosophy. Written and edited by a clinician-scientist in the field, this book remains an excellent user's guide to t
Author: Long-Biao Cui
Publisher: Frontiers Media SA
ISBN: 2832514502
Category : Science
Languages : en
Pages : 157
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Book Description
Author: Peter B. Barker
Publisher: Cambridge University Press
ISBN: 1107013399
Category : Medical
Languages : en
Pages : 373
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Book Description
This concise and comprehensive review uniquely contains all the information required to perform and interpret clinical MR perfusion imaging.
Author: Sanna Gevers
Publisher:
ISBN: 9789461911292
Category :
Languages : en
Pages : 170
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Book Description
Author: Danfeng Xie
Publisher:
ISBN:
Category :
Languages : en
Pages : 105
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Book Description
Arterial spin labeling (ASL) perfusion Magnetic Resonance Imaging (MRI) is a noninvasive technique for measuring quantitative cerebral blood flow (CBF) but subject to an inherently low signal-to-noise-ratio (SNR), resulting in a big challenge for data processing. Traditional post-processing methods have been proposed to reduce artifacts, suppress non-local noise, and remove outliers. However, these methods are based on either implicit or explicit models of the data, which may not be accurate and may change across subjects. Deep learning (DL) is an emerging machine learning technique that can learn a transform function from acquired data without using any explicit hypothesis about that function. Such flexibility may be particularly beneficial for ASL denoising. In this dissertation, three different machine learning-based methods are proposed to improve the image quality of ASL MRI: 1) a learning-from-noise method, which does not require noise-free references for DL training, was proposed for DL-based ASL denoising and BOLD-to-ASL prediction; 2) a novel deep learning neural network that combines dilated convolution and wide activation residual blocks was proposed to improve the image quality of ASL CBF while reducing ASL acquisition time; 3) a prior-guided and slice-wise adaptive outlier cleaning algorithm was developed for ASL MRI. In the first part of this dissertation, a learning-from-noise method is proposed for DL-based method for ASL denoising. The proposed learning-from-noise method shows that DL-based ASL denoising models can be trained using only noisy image pairs, without any deliberate post-processing for obtaining the quasi-noise-free reference during the training process. This learning-from-noise method can also be applied to DL-based ASL perfusion prediction from BOLD fMRI as ASL references are extremely noisy in this BOLD-to-ASL prediction. Experimental results demonstrate that this learning-from-noise method can reliably denoise ASL MRI and predict ASL perfusion from BOLD fMRI, result in improved signal-to-noise-ration (SNR) of ASL MRI. Moreover, by using this method, more training data can be generated, as it requires fewer samples to generate quasi-noise-free references, which is particularly useful when ASL CBF data are limited. In the second part of this dissertation, we propose a novel deep learning neural network, i.e., Dilated Wide Activation Network (DWAN), that is optimized for ASL denoising. Our method presents two novelties: first, we incorporated the wide activation residual blocks with a dilated convolution neural network to achieve improved denoising performance in term of several quantitative and qualitative measurements; second, we evaluated our proposed model given different inputs and references to show that our denoising model can be generalized to input with different levels of SNR and yields images with better quality than other methods. In the final part of this dissertation, a prior-guided and slice-wise adaptive outlier cleaning (PAOCSL) method is proposed to improve the original Adaptive Outlier Cleaning (AOC) method. Prior information guided reference CBF maps are used to avoid bias from extreme outliers in the early iterations of outlier cleaning, ensuring correct identification of the true outliers. Slice-wise outlier rejection is adapted to reserve slices with CBF values in the reasonable range even they are within the outlier volumes. Experimental results show that the proposed outlier cleaning method improves both CBF quantification quality and CBF measurement stability.
Author:
Publisher: Elsevier
ISBN: 0080861601
Category : Medical
Languages : en
Pages : 447
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Book Description
Progress in Brain Research is the most acclaimed and accomplished series in neuroscience. The serial is well-established as an extensive documentation of contemporary advances in the field. The volumes contain authoritative reviews and original articles by invited specialists. The rigorous editing of the volumes assures that they will appeal to all laboratory and clinical brain research workers in the various disciplines: neuroanatomy, neurophysiology, neuropharmacology, neuroendocrinology, neuropathology, basic neurology, biological psychiatry and the behavioral sciences.
Author: Jörn Huber
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Perfusion measurements in brain and liver are of high clinical interest. Arterial spin labeling (ASL) magnetic resonance imaging (MRI) has the potential to be an alternative to invasive measurements of perfusion using contrast agent-based techniques. However, the clinical application of ASL is currently limited due to a severe sensitivity to subject motion. The goal of this thesis was to develop novel methods which address the motion sensitivity of ASL sequences. The developed techniques include novel optimized approaches for background suppression, an automatic detection of breathholds during ASL experiments to suppress respiratory motion artifacts, prospective correction of respiratory motion during free-breathing scans as well as three-dimensional retrospective motion correction using a 3D GRASE PROPELLER (3DGP) readout. In addition, a novel 3DGP reconstruction, allowing joint estimation of motion and geometric distortion, is presented. Algorithms are implemented and validated in brain and liver ASL perfusion imaging using healthy volunteers. Finally, recommendations for future improvements of the developed techniques are given.
Author: James Duffin
Publisher: Frontiers Media SA
ISBN: 2832550215
Category : Science
Languages : en
Pages : 170
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Book Description
The acquisition of resting cerebral perfusion measures using magnetic resonance imaging (MRI) is one of the assessments of cerebrovascular health used to discern how well patients are coping with anatomical changes such as stenosis, and other factors impacting the supply of blood flow to the brain. Perfusion measures may be obtained using several MRI based techniques including arterial spin labeling (ASL) and dynamic contrast enhanced methods that rely on injected contrast agents such as gadolinium. Recently hypoxia-induced changes in deoxyhemoglobin have been used as a non-invasive contrast agent, measuring the resulting changes in blood oxygen dependent (BOLD) signals with MRI. With each approach, the means through which voxel-wise cerebral perfusion information is derived differs, leading to the development a variety of analysis methods in recent studies. This Research Topic is intended to attract manuscripts that advance the use of resting cerebral perfusion measures in clinical assessments of cerebrovascular health. In pursuit of this aim a better understanding of several aspects are needed.
