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SAMRI — Comprehensive Small Animal Magnetic Resonance Imaging Workflows

Horea-Ioan, Markus, Mehmet Fatih
2020 Zenodo  
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  
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]

Saman Sarraf, Mehdi Ostadhashem
2016 arXiv   pre-print
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

Serena Bonaretti, Garry E. Gold, Gary S. Beaupre, Ivan Olier
2020 PLoS ONE  
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]

S. Farrens, A. Grigis, L. El Gueddari, Z. Ramzi, Chaithya G. R., S. Starck, B. Sarthou, H. Cherkaoui, P.Ciuciu, J.-L. Starck
2019 arXiv   pre-print
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

Jiayu Fu, Hui Zhang, Kaiqi Wei, Chao Shi, Wei Zong, Valentina Hartwig
2022 Journal of Healthcare Engineering  
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

Robert D.M. Gray, Kim H. Parker, Michael A. Quail, Andrew M. Taylor, Giovanni Biglino
2016 MethodsX  
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

Karsten Tabelow, Brandon Whitcher
2011 Journal of Statistical Software  
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]

Pietro Cinaglia, Luciano Caroprese, Giuseppe Lucio Cascini, Francesco Dattola, Pasquale Iaquinta, Miriam Iusi, Pierangelo Veltri, Ester Zumpano
2018 Medical and Biological Image Analysis  
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

Stefan Appelhoff, Matthew Sanderson, Teon Brooks, Marijn van Vliet, Romain Quentin, Chris Holdgraf, Maximilien Chaumon, Ezequiel Mikulan, Kambiz Tavabi, Richard Höchenberger, Dominik Welke, Clemens Brunner (+4 others)
2019 Journal of Open Source Software  
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

Jan M. Binder, Alexander Stark, Nikolas Tomek, Jochen Scheuer, Florian Frank, Kay D. Jahnke, Christoph Müller, Simon Schmitt, Mathias H. Metsch, Thomas Unden, Tobias Gehring, Alexander Huck (+3 others)
2017 SoftwareX  
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

Julia M Huntenburg, Christopher J Steele, Pierre-Louis Bazin
2018 GigaScience  
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

D.J. Samatha Naidu, G. Anand Kumar Reddy
2021 International journal of computer science and mobile computing  
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

Michael Berks, Geoff Parker, Ross Little, Sue Cheung
2021 Journal of Open Source Software  
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

Markus J Ankenbrand, Liliia Shainberg, Michael Hock, David Lohr, Laura M Schreiber
2021 BMC Medical Imaging  
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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