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Automatic segmentation of white matter lesions in T1-weighted brain MR images

Songyang Yu, D.L. Pham, Dinggang Shen, E.H. Herskovits, S.M. Resnick, C. Davatzikos
Proceedings IEEE International Symposium on Biomedical Imaging  
White matter lesions are common brain abnormalities. In this paper, an automatic method for segmentation of white matter lesions in T1-weighted brain magnetic resonance (MR) images is presented.  ...  A patient's T1-weighted MR image is first segmented into the three major tissue types, white matter (WM), gray matter (GM) and cerebral spinal fluid (CSF) solely based on each voxel's intensity.  ...  CONCLUSIONS We have demonstrated a method for automatic segmentation of WM lesions in T1-weighted MR images in a stereotaxic space.  ... 
doi:10.1109/isbi.2002.1029241 dblp:conf/isbi/YuPSHRD02 fatcat:mpszvo5ar5auncerubhgjzzljm

Automated Bayesian Segmentation of Microvascular White-Matter Lesions in the ACCORD-MIND Study

E Herskovits, R Bryan, F Yang
2008 Advances in Medical Sciences  
In this manuscript we describe the design and evaluation of a Bayesian lesion-segmentation method, with the expectation that our approach would segment white-matter brain lesions in MR images without user  ...  In this manuscript we describe the design and evaluation of a Bayesian lesion-segmentation method, with the expectation that our approach would segment white-matter brain lesions in MR images without user  ...  ACKNOWLEDGEMENTS The work was supported by the National Institutes of Health (NIH) under grant R01 AG13743, which is funded by the National Institute of Aging, the National Institute of Mental health,  ... 
doi:10.2478/v10039-008-0039-3 pmid:18842559 fatcat:qpcd5kxn5bfktnrwdcgxntee2m

White Matter Lesion Segmentation from Volumetric MR Images [chapter]

Faguo Yang, Tianzi Jiang, Wanlin Zhu, Frithjof Kruggel
2004 Lecture Notes in Computer Science  
In this paper, we introduce an automatic algorithm for segmentation of white matter lesions from volumetric MR images.  ...  White matter lesions are common pathological findings in MR tomograms of elderly subjects. These lesions are typically caused by small vessel diseases (e.g., due to hypertension, diabetes).  ...  The main obstacle to white matter lesion segmentation is that the intensities of white matter lesions and gray matter are very similar in T1-weighted images , therefore they can not be distinguished only  ... 
doi:10.1007/978-3-540-28626-4_14 fatcat:pheiu6hrivg27jjrw6bw3ddy2i

Fully automatic detection of deep white matter T1 hypointense lesions in multiple sclerosis

Lothar Spies, Anja Tewes, Per Suppa, Roland Opfer, Ralph Buchert, Gerhard Winkler, Alaleh Raji
2013 Physics in Medicine and Biology  
A novel method is presented for fully automatic detection of candidate white matter (WM) T1 hypointense lesions in three-dimensional high-resolution T1weighted magnetic resonance (MR) images.  ...  By definition, T1 hypointense lesions have similar intensity as gray matter (GM) and thus appear darker than surrounding normal WM in T1-weighted images.  ...  Acknowledgments LS, AT, RO and PS are employees of jung diagnostics GmbH. RB, AR and GW have nothing to disclose.  ... 
doi:10.1088/0031-9155/58/23/8323 pmid:24216694 fatcat:7i3tawqwynaezfxbbwqpdzfpou

sj-pdf-1-mso-10.1177_2055217320964502 - Supplemental material for Enlarged perivascular spaces are not associated with vascular co-morbidities, clinical outcomes, and brain volumes in people with secondary progressive multiple sclerosis

Lindsey Wooliscroft, Erin Boespflug, Andrea Hildebrand, Kathleen Shangraw, Elizabeth Silbermann, Dennis Bourdette, Rebecca Spain
2020 Figshare  
Supplemental material, sj-pdf-1-mso-10.1177_2055217320964502 for Enlarged perivascular spaces are not associated with vascular co-morbidities, clinical outcomes, and brain volumes in people with secondary  ...  progressive multiple sclerosis by Lindsey Wooliscroft Dennis Bourdette and Rebecca Spain in Multiple Sclerosis Journal – Experimental, Translational and Clinical  ...  MTR, DTI, T1-RT, T2-RT, T2*, T2', 1 H-MRS, perfusion, Na) Type (e.g. whole brain, grey matter, white matter, spinal cord, normal-appearing grey matter or white matter) NA Freesurfer image analysis suite  ... 
doi:10.25384/sage.13089643.v1 fatcat:c7shoaibn5dtrh7qtqkzn4iwmi

Segmentation of White Matter Lesions from Volumetric MR Images [chapter]

S. A. Hojjatoleslami, F. Kruggel, D. Y. von Cramon
1999 Lecture Notes in Computer Science  
To achieve an accurate quantification, an algorithm is proposed for automatic segmentation of white matter atrophies and lesions from T1-weighted 3D Magnetic Resonance (MR) images of the head.  ...  The method is fully applied to detect the white matter lesions and relevant structures from a set of 41 MR images of normal and pathological subjects.  ...  Gertz from Department of Psychiatry, University Clinic Leipzig, for providing the data.  ... 
doi:10.1007/10704282_6 fatcat:lziryquysngrdojfjqadpeqxqy

Automatic segmentation of brain tissues and MR bias field correction using a digital brain atlas [chapter]

Koen Van Leemput, Frederik Maes, Dirk Vandermeulen, Paul Suetens
1998 Lecture Notes in Computer Science  
This paper 1 proposes a method for fully automatic segmentation of brain tissues and MR bias field correction using a digital brain atlas.  ...  The method can handle multi-channel data and slice-per-slice constant offsets, and is fully automatic due to the use of a digital brain atlas.  ...  Acknowledgments This research was performed within the context of the BIOMORPH project "Development and Validation of techniques for Brain Morphometry" supported by the European Commission under contract  ... 
doi:10.1007/bfb0056312 fatcat:2pgqgbvucjhxbfoupw4ww5jjcq

Automated Segmentation of MS Lesions from Multi-channel MR Images [chapter]

Koen Van Leemput, Frederik Maes, Fernando Bello, Dirk Vandermeulen, Alan Colchester, Paul Suetens
1999 Lecture Notes in Computer Science  
This paper describes a fully automated model-based method for segmentation of MS lesions from multi-channel MR images.  ...  Quantitative analysis of MR images is becoming increasingly important as a surrogate marker in clinical trials in multiple sclerosis (MS).  ...  Acknowledgments This work was supported by the EC-funded BIOMORPH project 95-0845, a collaboration between the Universities of Kent and Oxford (UK), ETH Zürich  ... 
doi:10.1007/10704282_2 fatcat:fdraejgs2vdvbeyycprx6uhiyy

Lesion-Function Analysis from Multimodal Imaging and Normative Brain Atlases for Prediction of Cognitive Deficits in Glioma Patients

Martin Kocher, Christiane Jockwitz, Philipp Lohmann, Gabriele Stoffels, Christian Filss, Felix M. Mottaghy, Maximilian I. Ruge, Carolin Weiss Lucas, Roland Goldbrunner, Nadim J. Shah, Gereon R. Fink, Norbert Galldiks (+2 others)
2021 Cancers  
Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and FET-PET positive tumor sites were semi-automatically segmented and elastically registered to a normative, resting state (RS) fMRI-based  ...  functional cortical network atlas and to the JHU atlas of white matter (WM) tracts, and their influence on cognitive test scores relative to a cohort of matched healthy subjects was assessed.  ...  segmented resection cavity; T1-CE: semi-automatically segmented contrast-enhancing regions in T1-weighted MR images; FET-PET: semi-automatically segmented FET-PET-positive lesions; DMN: default mode network  ... 
doi:10.3390/cancers13102373 pmid:34069074 fatcat:b7b66s2rdzdivbwltitzhw2i4m

MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Adriënne M. Mendrik, Koen L. Vincken, Hugo J. Kuijf, Marcel Breeuwer, Willem H. Bouvy, Jeroen de Bresser, Amir Alansary, Marleen de Bruijne, Aaron Carass, Ayman El-Baz, Amod Jog, Ranveer Katyal (+18 others)
2015 Computational Intelligence and Neuroscience  
We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain  ...  Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others.  ...  The authors would like to acknowledge the following members of the Utrecht Vascular Cognitive Impairment Study Group who were not included as coauthors of this paper but were involved in the recruitment  ... 
doi:10.1155/2015/813696 pmid:26759553 pmcid:PMC4680055 fatcat:uhsmxrfz65ahtc7fciqt6v3fem

Use Case I: Imaging Biomarkers in Neurological Disease. Focus on Multiple Sclerosis [chapter]

Diana M. Sima, Dirk Loeckx, Dirk Smeets, Saurabh Jain, Paul M. Parizel, Wim Van Hecke
2016 Imaging Biomarkers  
is basically derived from T1-weighted image segmentation.  ...  Lesion-TOADS [ 52 ] , on the other hand, employs a sophisticated mechanism of combining information from different MR sequences (T1-weighted, T2, PD or FLAIR) in order to simultaneously segment lesions  ... 
doi:10.1007/978-3-319-43504-6_15 fatcat:jjue6uryjba3vpnm3eblmlauge

An Approach of Segmenting Brain Tumor using Self Organising Map

Hemanandhini Dharshini.
2016 International Journal of Advanced Research  
segment brain tumors and lesions in MR images.  ...  In this work Thresholding algorithms are used to segment the grey matters and the white matters of the brain.  ... 
doi:10.21474/ijar01/770 fatcat:eiy5qojv65ddhihcg5kd4z4p6u

Evaluation of an automatic brain segmentation method developed for neonates on adult MR brain images

Pim Moeskops, Max A. Viergever, Manon J. N. L. Benders, Ivana Išgum, Sébastien Ourselin, Martin A. Styner
2015 Medical Imaging 2015: Image Processing  
Automatic brain tissue segmentation is of clinical relevance in images acquired at all ages.  ...  Recently, a method for automatic brain segmentation in preterm infants has been developed, of which a preliminary version was presented by Chiţǎ et al. 7 The most recent version of this method has been  ...  The images were registered to the FLAIR images, and bias-corrected using SPM8. 8 Manual annotations of cortical grey matter, basal ganglia, white matter, white matter lesions, cerebrospinal fluid in the  ... 
doi:10.1117/12.2081833 dblp:conf/miip/MoeskopsVBI15 fatcat:pvti5e647fb7dbq24d55fmjrwi

Automatic Brain and Tumor Segmentation [chapter]

Nathan Moon, Elizabeth Bullitt, Koen van Leemput, Guido Gerig
2002 Lecture Notes in Computer Science  
Our driving application is the segmentation of brain tissue and tumors from three-dimensional magnetic resonance imaging (MRI).  ...  Combining image segmentation based on statistical classification with a geometric prior has been shown to significantly increase robustness and reproducibility.  ...  [14] , [15] developed automatic segmentation of MR images of normal brains by statistical classification, using an atlas prior for initialization and also for geometric constraints.  ... 
doi:10.1007/3-540-45786-0_46 fatcat:oyskexvmdjc7nkknv6wb2sjmvi

Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI

Ying Wu, Simon K. Warfield, I. Leng Tan, William M. Wells, Dominik S. Meier, Ronald A. van Schijndel, Frederik Barkhof, Charles R.G. Guttmann
2006 NeuroImage  
Materials and methods: Proton density-, T2-and contrast-enhanced T1-weighted brain images of 12 MR scans were pre-processed through intracranial cavity (IC) extraction, inhomogeneity correction and intensity  ...  Purpose: To automatically segment multiple sclerosis (MS) lesions into three subtypes (i.e., enhancing lesions, T1 "black holes", T2 hyperintense lesions).  ...  This work was supported in parts by a grant from the U.S.  ... 
doi:10.1016/j.neuroimage.2006.04.211 pmid:16797188 fatcat:hbbtiadvwjawreq2aroojfjbxm
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