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SAMRI — Comprehensive Small Animal Magnetic Resonance Imaging Workflows
2020
Zenodo
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Magnetic Resonance Imaging (MRI) is a measurement method with high depth penetration, which enjoys extensive use in imaging organs with an intricate holistic mode of function, such as the brain. ...
A core challenge in the analysis of preclinical MRI data is the adaptation of existing toolkits, designed primarily for human use, to the constraints and capabilities accessible in small animals. ...
We are drafting a full length article detailing the package. standards-compliant integration of small animal magnetic resonance imaging data," Frontiers in neuroinformatics, vol. 14, p. 5, Feb. 2020. ...
doi:10.5281/zenodo.4064658
fatcat:gpihd5vfhbdwdlamcm5tri77gq
Denoising in Magnetic Resonance Images using Improved Gaussian Smoothing Technique
2019
International journal of recent technology and engineering
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Magnetic Resonance Images (MRI) are usually prone to noise like Rician and Gaussian noise. It is very difficult to perform image processing functions with the presence of noise. ...
The input RGB image is first converted to gray scale image in which the contrast, sharpness, shadow and structure of the color of image are preserved. ...
NOISE MODELS Magnetic Resonance Images are mainly affected by two main types of noise namely Rician and Gaussian noise.
3.1.Rician Noise: Magnetic Resonance Images are affected by Rician noise which ...
doi:10.35940/ijrte.b2859.078219
fatcat:qpxbtoav7fh4rkqlhomdozsd5a
Big Data Spark Solution for Functional Magnetic Resonance Imaging
[article]
2016
arXiv
pre-print
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In this paper, we designed, developed and successfully tested a new pipeline for medical imaging data (especially functional magnetic resonance imaging - fMRI) using Big Data Spark / PySpark platform on ...
A huge amount of 3D and 4D images are acquired in different forms and resolutions using a variety of medical imaging modalities. ...
Cristina Saverino Post-doctoral fellowship at Toronto Rehabilitation Institute-University Health Network for extending their help and support in this study. ...
arXiv:1603.07064v1
fatcat:pt2wcx4w3jce7c7bk65xbimav4
pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage
2020
PLoS ONE
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To study cartilage degeneration, researchers have developed algorithms to segment femoral knee cartilage from magnetic resonance (MR) images and to measure cartilage morphology and relaxometry. ...
; and 3) analysis of cartilage morphology and relaxometry. ...
Seiler for software engineering support, Amy Silder, Julie Kolesar, and Scott Uhlrich for beta testing, Susan Holmes, Felix Ambellan, and Yolanda Gil for their feedbacks on the first preprint version of ...
doi:10.1371/journal.pone.0226501
pmid:31978052
fatcat:hexft5jsyvf4zjfdbun2u6mmsa
PySAP: Python Sparse Data Analysis Package for Multidisciplinary Image Processing
[article]
2019
arXiv
pre-print
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We present the open-source image processing software package PySAP (Python Sparse data Analysis Package) developed for the COmpressed Sensing for Magnetic resonance Imaging and Cosmology (COSMIC) project ...
In this paper we present the features available in PySAP and provide practical demonstrations on astrophysical and magnetic resonance imaging data. ...
Acknowledgments The authors wish to acknowledge the COSMIC project funded by the CEA DRF-Impulsion call in 2016, the Uni-vEarthS Labex program of Sorbonne Paris Cite (ANR-10-LABX-0023 and ANR-11-IDEX-0005 ...
arXiv:1910.08465v1
fatcat:ms42y3gvbfdnrjpcvplr4dxx3i
Design and Performance Analysis of a Dynamic Magnetic Resonance Imaging-Compatible Device for Triangular Fibrocartilage Complex Injury Diagnosis
2022
Journal of Healthcare Engineering
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As such, this study presents the design and evaluation of a dynamic magnetic resonance imaging (MRI) auxiliary tool for TFCC injury diagnosis. ...
According to the MRI contrast test results, the image quality score of patients wearing the auxiliary device is higher than for those without. ...
In recent years, dynamic magnetic resonance imaging (DMRI) technology has been developed and applied in clinical settings. ...
doi:10.1155/2022/9688441
fatcat:lehoiwte2fgdhdswyarzec32yq
A method to implement the reservoir-wave hypothesis using phase-contrast magnetic resonance imaging
2016
MethodsX
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A method to implement the reservoir-wave hypothesis using phasecontrast magnetic resonance imaging. MethodsX, 3, 508-512. ...
General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: ...
A R T I C L E I N F O
Method name: Implementation of the reservoir-wave hypothesis using phase-contrast magnetic resonance imaging
Keywords: Hemodynamics, Wave intensity analysis, Windkessel, Magnetic ...
doi:10.1016/j.mex.2016.08.004
pmid:28003965
pmcid:PMC5156381
fatcat:j2zrmgwgpfgprj3zcx5fpw7be4
Special Volume on Magnetic Resonance Imaging inR
2011
Journal of Statistical Software
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The special volume on "Magnetic Resonance Imaging in R" features articles and packages related to a variety of imaging modalities: functional MRI, diffusion-weighted MRI, dynamic contrast-enhanced MRI, ...
Outlook We hope to provide with this Special Volume of Journal of Statistical Software a worthwhile collection of activity in the field of magnetic resonance imaging in R. ...
The mathematical formalism and fast imaging techniques introduced by Mansfield, in combination with Lauterbur's work, started the scientific development of magnetic resonance imaging (MRI). ...
doi:10.18637/jss.v044.i01
fatcat:fccdy4caabfo7j24omkkp5xcm4
Bioinformatics Solutions for Image Data Processing
[chapter]
2018
Medical and Biological Image Analysis
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In medicine, computational platforms generate high amount of data from medical devices such as Computed Tomography (CT), and Magnetic Resonance Imaging (MRI); this chapter will survey on bioinformatics ...
solutions and toolkits for medical imaging in order to suggest an overview of techniques and methods that can be applied for the imaging analysis in medicine. ...
The increasing adoption in the clinical practice of the 3D solutions, due also to the evolution of technologies in medical imaging such as the Computed Tomography (CT) and the Magnetic Resonance Imaging ...
doi:10.5772/intechopen.76459
fatcat:kejwf2t3rrcjnccmad4d2jskwa
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis
2019
Journal of Open Source Software
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National Institute of Mental Health (1R24MH114705), the Bezos Family Foundation, the Simms Mann Foundation, and the Google Summer of Code 2019. ...
Acknowledgements MNE-BIDS development is partly supported by the Academy of Finland (grant 310988), NIH NINDS R01-NS104585, ERC Starting Grant SLAB ERC-YStG-676943, ANR meegBIDS.fr, BRAIN Initiative and ...
In addition to this core functionality, MNE-BIDS is continuously being extended to facilitate the analysis of BIDS formatted data. ...
doi:10.21105/joss.01896
fatcat:qz6p6mb6cvagvdfo2c72lrpaha
Qudi: A modular python suite for experiment control and data processing
2017
SoftwareX
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Qudi is a general, modular, multi-operating system suite written in Python 3 for controlling laboratory experiments. ...
It provides a structured environment by separating functionality into hardware abstraction, experiment logic and user interface layers. ...
Acknowledgments We would like to thank Boris Naydenov for advocating the use of a software platform that can be used by the whole Quantum Optics institute and for maintaining the predecessor to this software ...
doi:10.1016/j.softx.2017.02.001
fatcat:3opjee77gretvfygowqhrgxwam
Nighres: processing tools for high-resolution neuroimaging
2018
GigaScience
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With recent improvements in human magnetic resonance imaging (MRI) at ultra-high fields, the amount of data collected per subject in a given MRI experiment has increased considerably. ...
With these tools, segmentation and laminar analysis of cortical MRI data can be performed at resolutions up to 500 μm in reasonable times. ...
Background Recent advances in ultra-high field (7 Tesla [T] and above) magnetic resonance imaging (MRI) make it possible to image the entire human brain at an unprecedented level of detail [1] . ...
doi:10.1093/gigascience/giy082
pmid:29982501
pmcid:PMC6065481
fatcat:25cuv6slgzgddeaky2srkg7fua
EARLIER DETECTION OF ALZHEIMER'S DISEASE USING IMAGE PROCESSING AND MACHINE LEARNING ALGORITHMS WITH GRAPH THEORY
2021
International journal of computer science and mobile computing
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The study of brain network based on resting-state functional Magnetic Resonance Imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because ...
4D images. ...
The importance of such approaches is highlighted in the context of Magnetic Resonance (M.R.) brain image classification and segmentation. ...
doi:10.47760/ijcsmc.2021.v10i08.006
fatcat:zgt4ttu2knesrhhtn5u2rf5q3a
Madym: A C++ toolkit for quantitative DCE-MRI analysis
2021
Journal of Open Source Software
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In dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) a sequence of MRI images are acquired to measure the passage of a contrast-agent within a tissue of interest. ...
Berks, 2021b)) and python (integrated with the main toolkit), that allow the flexibility of developing in those scripting languages, while allowing C++ to do the heavy-duty computational work of tracer-kinetic ...
While working on Madym, Michael Berks was funded by the following grants: Cancer Research UK (CRUK) Clinician Scientist award (grant C19221/A22746); CRUK and EPSRC Cancer Imaging Centre in Cambridge and ...
doi:10.21105/joss.03523
fatcat:mf4uzrzhgncvtfvj2bripkavne
Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI
2021
BMC Medical Imaging
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We demonstrate this in two case studies on cardiac magnetic resonance imaging. ...
Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. ...
On the one hand there is a public dataset of cardiac magnetic resonance images, the Data Science Bowl Cardiac Challenge (DSBCC) data [33] . ...
doi:10.1186/s12880-021-00551-1
pmid:33588786
pmcid:PMC7885570
fatcat:m2y4psjgsfcjvddhk67ul5ibmu
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