scholarly journals Fast method for brain image segmentation: Application to proton magnetic resonance spectroscopic imaging

2005 ◽  
Vol 54 (5) ◽  
pp. 1268-1272 ◽  
Author(s):  
David Bonekamp ◽  
Alena Horská ◽  
Michael A. Jacobs ◽  
Atilla Arslanoglu ◽  
Peter B. Barker
Keyword(s):  
Image Segmentation ◽  
Magnetic Resonance ◽  
Proton Magnetic Resonance ◽  
Spectroscopic Imaging ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Fast Method ◽  
Brain Image ◽  
Brain Image Segmentation

Grey matter abnormalities in multiple sclerosis: proton magnetic resonance spectroscopic imaging

2001 ◽  
Vol 7 (4) ◽  
pp. 221-226 ◽  
Author(s):  
Rakesh Sharma ◽  
Ponnada A Narayana ◽  
Jerry S Wolinsky
Keyword(s):  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Proton Magnetic Resonance ◽  
Magnetization Transfer ◽  
Spectroscopic Imaging ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Relapsing Remitting ◽  
Cortical Gray Matter ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Characteristics

Pathologically defined abnormalities in the cortical gray matter (GM) are well described in multiple sclerosis (MS) but are infrequently seen by conventional magnetic resonance imaging (MRI). We systematically evaluated 52 relapsing - remitting MS patients and 20 normal volunteers with high resolution MRI and short echo proton magnetic resonance spectroscopic imaging (MRSI). Individual tissue contributions to the spectroscopic voxels were estimated based on MRI that incorporated both CSF suppression and magnetization transfer, or double inversion images in which both CSF and GM were suppressed. Strong resonances in the 0.8 to 1.5 p.p.m. spectral region were observed in 13 MS patients. Image segmentation based on the MRI characteristics of tissues contributing to the spectroscopic voxels showed that these additional peaks originated mainly from GM. The presence of these additional peaks suggests that the normal appearance GM on MRI, is biochemically abnormal in a substantial proportion of relapsing-remitting MS patients.

Distance metric-based time-efficient fuzzy algorithm for abnormal magnetic resonance brain image segmentation

2012 ◽  
Vol 22 (5) ◽  
pp. 1013-1022 ◽  
Author(s):  
D. Jude Hemanth ◽  
C. Kezi Selva Vijila ◽  
A. Immanuel Selvakumar ◽  
J. Anitha
Keyword(s):  
Image Segmentation ◽  
Magnetic Resonance ◽  
Distance Metric ◽  
Fuzzy Algorithm ◽  
Brain Image ◽  
Brain Image Segmentation

Proton magnetic resonance spectroscopic imaging of human breast cancer: A preliminary study

2003 ◽  
Vol 19 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Michael A. Jacobs ◽  
Peter B. Barker ◽  
Paul A. Bottomley ◽  
Zaver Bhujwalla ◽  
David A. Bluemke
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance ◽  
Human Breast Cancer ◽  
Proton Magnetic Resonance ◽  
Spectroscopic Imaging ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Human Breast ◽  
Preliminary Study

scholarly journals ORYX-MRSI: A Fully-Automated Open-Source Software for Three-Dimensional Proton Magnetic Resonance Spectroscopic Imaging Data Analysis

2021 ◽  
Author(s):  
Sevim Cengiz ◽  
Muhammed Yildirim ◽  
Abdullah Bas ◽  
Esin Ozturk-Isik
Keyword(s):  
Data Analysis ◽  
Magnetic Resonance ◽  
Chemical Shift ◽  
Open Source ◽  
Proton Magnetic Resonance ◽  
Spectroscopic Imaging ◽  
Brain Atlas ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Spectral Quality ◽  
Chemical Shift Artifact

Proton magnetic resonance spectroscopic imaging (1H-MRSI) provides noninvasive evaluation of brain metabolism. However, there are some limitations of 1H-MRSI preventing its wider use in the clinics, including the spectral quality issues, partial volume effect and chemical shift artifact. Additionally, it is necessary to create metabolite maps for analyzing spectral data along with other MRI modalities. In this study, a MATLAB-based open-source data analysis software for 3D 1H-MRSI, called Oryx-MRSI, which includes modules for visualization of raw 1H-MRSI data and LCModel outputs, chemical shift correction, tissue fraction calculation, metabolite map production, and registration onto standard MNI152 brain atlas while providing automatic spectral quality control, is presented. Oryx-MRSI implements region of interest analysis at brain parcellations defined on MNI152 brain atlas. All generated metabolite maps are stored in NIfTI format. Oryx-MRSI is publicly available at https://github.com/sevimcengiz/Oryx-MRSI along with six example datasets.

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