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Segmentation of multiple sclerosis lesions in intensity corrected multispectral MRI

B. Johnston, M.S. Atkins, B. Mackiewich, M. Anderson
1996 IEEE Transactions on Medical Imaging  
to the intermediate segmentation in order to develop a mask image containing only white matter and Multiple Sclerosis (MS) lesion.  ...  Abstruct-To segment brain tissues in magnetic resonance images of the brain, we have implemented a stochastic relaxation method which utilizes partial volume analysis for every brain voxel, and operates  ...  Rhodes of the University of British Columbia MSNRI Group for supplying the MFU data and the manually drawn lesions on which the algorithm was tested. They also thank M.  ... 
doi:10.1109/42.491417 pmid:18215898 fatcat:42ljwonkwbdbfdblg7emqhj6em

Use of MRI to Measure Whole Brain Atrophy in MS Patients

P. Mazgaj, Z. Drzazga, I. Karpiel, A. Giec-Lorenz, E. Krzystanek
2018 Acta Physica Polonica. A  
An usability of Lesion Segmentation Tool toolbox in process of automatic detection and segmentation T2 hyperintense lesions in FLAIR images is discussed.  ...  Pathological brain tissue loss can be described in terms of change in the brain parenchymal fraction (BPF).  ...  In brain MRI, segmentation of brain tissues is an important step for numerical application.  ... 
doi:10.12693/aphyspola.133.725 fatcat:hns2wwc2ejeave7egzua5fykae

BRAIM: A computer-aided diagnosis system for neurodegenerative diseases and brain lesion monitoring from volumetric analyses

Sandra Morales, Angela Bernabeu-Sanz, Fernando López-Mir, Pablo González, Luis Luna, Valery Naranjo
2017 Computer Methods and Programs in Biomedicine  
In addition to be used to quantify treatment effectiveness in patients with brain lesions, it was demonstrated that BRAIM is able to classify a subject according to the brain volume measurements using  ...  Specifically, three types of measurements can be performed: (1) total volume of white, gray matter and cerebrospinal fluid; (2) brain structure volumes (volume of putamen, thalamus, hippocampus and caudate  ...  The MR brain data sets and their manual segmentations used for brain tissue validation were provided by the Center for Morphometric Analysis at  ... 
doi:10.1016/j.cmpb.2017.04.006 pmid:28552122 fatcat:qbwny5ukl5es7nz3oj6jbdchvq

Repeatability and reproducibility of FreeSurfer, FSL-SIENAX and SPM brain volumetric measurements and the effect of lesion filling in multiple sclerosis

Chunjie Guo, Daniel Ferreira, Katarina Fink, Eric Westman, Tobias Granberg
2018 European Radiology  
SPM-based methods overall provide the most robust segmentations (except white matter segmentations on different scanners where FreeSurfer is more robust). • MS lesion filling with Lesion Segmentation Toolbox  ...  The whole-brain, grey matter (GM) and white matter (WM) volumes were calculated with and without normalisation to the intracranial volume or FSL-SIENAX scaling factor.  ...  Acknowledgements We would like to thank the participants and their families as well as the staff at the MRI at Karolinska University Hospital in Huddinge for making this study possible.  ... 
doi:10.1007/s00330-018-5710-x pmid:30242503 fatcat:c6kde6yl5ndlpevowiz7zbdwte

System for Integrated Neuroimaging Analysis and Processing of Structure

Bennett A. Landman, John A. Bogovic, Aaron Carass, Min Chen, Snehashis Roy, Navid Shiee, Zhen Yang, Bhaskar Kishore, Dzung Pham, Pierre-Louis Bazin, Susan M. Resnick, Jerry L. Prince
2012 Neuroinformatics  
Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to  ...  Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific  ...  SINAPS uses multiple MR images to segment both normal brain tissue and white matter lesion while preserving topology.  ... 
doi:10.1007/s12021-012-9159-9 pmid:22932976 pmcid:PMC3511612 fatcat:krgqmregs5hqnm3isklageiqi4

Partial volume segmentation in 3D of lesions and tissues in magnetic resonance images

Brian Johnston, M. Stella Atkins, Kellogg S. Booth, Murray H. Loew
1994 Medical Imaging 1994: Image Processing  
The algorithm has been used to segment dual echo MRI data sets of Multiple Sclerosis patients using lesions, gray matter, white matter, and cerebrospinal fluid as the partial volume constituents.  ...  The results of the application of the algorithm to these datasets is presented and compared to the manual lesion segmentations of the same data.  ...  The authors wish to thank the University ofBritish ColumbiaMSfMRJ Group for supplying the MRI data on which the algorithm was tested.  ... 
doi:10.1117/12.175075 fatcat:tlpfrl2xefgizi4b224zuvz53e

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

P.R.B. Diniz, L.O. Murta-Junior, D.G. Brum, D.B. de Araújo, A.C. Santos
2010 Brazilian Journal of Medical and Biological Research  
Tissue classification Following the previously described pre-processing step, the encephalon extracted from MRI was segmented into different brain tissues (white matter, gray matter and CSF) by the use  ...  The image without the CSF is submitted again to the algorithm of maximum entropy and gray matter is segmented. Once the gray matter is subtracted, one ends with the white matter.  ... 
doi:10.1590/s0100-879x2009007500019 pmid:19936540 fatcat:jtxewakecjfwvht7545keizx5u

Ex Vivo MRI Analytical Methods and Brain Pathology in Preterm Lambs Treated with Postnatal Dexamethasone †

Nathanael J. Yates, Kirk W. Feindel, Andrew Mehnert, Richard Beare, Sophia Quick, Dominique Blache, J. Jane Pillow, Rod W. Hunt
2020 Brain Sciences  
Spontaneous lesions detected in the white matter of the frontal cortex, temporo-parietal cortex, occipital lobe, and deep to the parahippocampal gyrus were confirmed with histology.  ...  Neither postnatal dexamethasone treatment nor gestation showed any associations with lesion incidence, frontal cortex (total, white, or grey matter) or hippocampal volume (all p > 0.05).  ...  Acknowledgments: Ellen Williams is thanked for preparing the tissue used for histology.  ... 
doi:10.3390/brainsci10040211 pmid:32260193 fatcat:slnebbwarrfqdgwms7piouiphi

MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients

Francesco La Rosa, Thomas Yu, Germán Barquero, Jean-Philippe Thiran, Cristina Granziera, Meritxell Bach Cuadra
2021 Computers in Biology and Medicine  
These images were then compared to the real MP2RAGE UNI (considered as ground truth) analyzing the output of automatic brain tissue and lesion segmentation tools.  ...  brain tissue and lesion contrast in multiple sclerosis (MS) patients.  ...  We acknowledge access to the facilities and expertise of the CIBM Center for Biomedical Imaging, a Swiss research center of excellence founded and supported by Lausanne University Hospital (CHUV), University  ... 
doi:10.1016/j.compbiomed.2021.104297 pmid:33711559 fatcat:t4z4zjcb7vbgth2glmmacuqcoq

Shape and Volume of Lacunar Infarcts: A 3D MRI Study in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy

D. Herve, J.-F. Mangin, N. Molko, M.-G. Bousser, H. Chabriat
2005 Stroke  
The segmentation of lacunar infarcts appears promising to better understand the pathophysiology of tissue lesions secondary to small vessel diseases. (Stroke. 2005;36:2384-2388.)  ...  Recent imaging techniques based on triangulation and connectivity can now be used for 3D segmentation of cerebral lesions.  ...  Segmentation and 3D Analysis of Lacunar Cavities Image postprocessing was performed using the Anatomist software dedicated to MRI segmentation of the brain (developed by CEA).  ... 
doi:10.1161/01.str.0000185678.26296.38 pmid:16224090 fatcat:xk4j6f2duzewtav42lusek5obq

MRI segmentation analysis in temporal lobe and idiopathic generalized epilepsy

Hila Goldberg, Arie Weinstock, Niels Bergsland, Michael G Dwyer, Osman Farooq, Mona Sazgar, Guy Poloni, Cierra Treu, Bianca Weinstock-Guttman, Murali Ramanathan, Robert Zivadinov
2014 BMC Neurology  
Methods: TLE patients were classified in TLE lesional (L-TLE) or non-lesional (NL-TLE) based on presence or absence of MRI temporal structural abnormalities.  ...  Normal brain volume (NBV), normal grey matter volume (NGMV), normal white matter volume (NWMV), and volumes of subcortical deep grey matter structures were quantified.  ...  Extensive white matter tracts abnormalities on DTI were identified also in JME [44] .  ... 
doi:10.1186/1471-2377-14-131 pmid:24938118 pmcid:PMC4070342 fatcat:omqhy3e6kvcyfmtw2uputbzt5i

Tumor Detection in MRI Brain Images Based on Saliency Computational Modeling

Muwei Jian, Xianxin Zhang, Lifu Ma, Hui Yu
2020 IFAC-PapersOnLine  
Finally, the results are further improved by denoising, segmentation and morphological operations. Experiments performed on MRI brain images show that the proposed method is useful and effective.  ...  In this paper, we propose a tumor detection method based on saliency modeling for MRI brain images.  ...  Brain tissue can be divided into white matter (White Matter, WM), gray matter (Gray Matter, GM) and cerebrospinal fluid (Cerebro-Spinal Fluid (CSF)).  ... 
doi:10.1016/j.ifacol.2021.04.123 fatcat:alvkbjivuvhtdc2rrsbdhe6miy

Segmentation of brain magnetic resonance images for measurement of gray matter atrophy in multiple sclerosis patients

Kunio Nakamura, Elizabeth Fisher
2009 NeuroImage  
Multiple sclerosis (MS) affects both white matter and gray matter (GM).  ...  Measurement of GM volumes is a particularly useful method to estimate the total extent of GM tissue damage because it can be done with conventional magnetic resonance images (MRI).  ...  The authors would like to thank Patricia Jagodnik for the help with image data management and Smitha Thomas for evaluation of gray matter segmentation results.  ... 
doi:10.1016/j.neuroimage.2008.09.059 pmid:19007895 pmcid:PMC3001325 fatcat:6gcxdoashbcclkbps6upsi2bii

Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images

Ayush Goyal, Sunayana Tirumalasetty, Gahangir Hossain, Rajab Challoo, Manish Arya, Rajeev Agrawal, Deepak Agrawal
2019 Journal of Healthcare Engineering  
or researchers in the field to perform automatic segmentation of gray and white matter regions in brain MRI images.  ...  This tool provides the user automatized functionality to perform automatic segmentation and extract the gray and white matter regions of patient brain image data using an algorithm called adapted fuzzy  ...  Imaging (LONI) provided by the University of Southern California (USC) for providing brain MRI patient data and for sharing the neurological data in this project.  ... 
doi:10.1155/2019/9610212 pmid:30906515 pmcid:PMC6393878 fatcat:yrvkbcfw35ho5acc6nl6o2mwsi

Risk Factors of Restroke in Patients with Lacunar Cerebral Infarction Using Magnetic Resonance Imaging Image Features under Deep Learning Algorithm

Chunli Ma, Hong Li, Kui Zhang, Yuzhu Gao, Lei Yang, Yuvaraja Teekaraman
2021 Contrast Media & Molecular Imaging  
This study was aimed to explore the magnetic resonance imaging (MRI) image features based on the fuzzy local information C-means clustering (FLICM) image segmentation method to analyze the risk factors  ...  The proportion of patients with a history of hypertension, the proportion of patients with paraventricular white matter lesion (WML) score greater than 2 in the stroke group, the proportion of patients  ...  (CNN) segmentation of brain tissue MRI images of the brain white matter Jaccard coefficients (Figure 4 ).  ... 
doi:10.1155/2021/2527595 pmid:34887708 pmcid:PMC8616697 fatcat:e2jdtz7wgbbqnaghgsrlf3hygy
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