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Automated White Matter Lesion Segmentation by Voxel Probability Estimation [chapter]

Petronella Anbeek, Koen Vincken, Matthias van Osch, Bob Bisschops, Max Viergever, Jeroen van der Grond
2003 Lecture Notes in Computer Science  
A new method for fully automated segmentation of white matter lesions (WMLs) on cranial MR imaging is presented. The algorithm uses five types of regular MRI-scans.  ...  The technique generates images representing the probability per voxel being part of a WML. By application of thresholds on these probability maps binary segmentations are produced.  ...  Moreover, since the method has a general basis it is applicable to many other segmentation problems, for instance segmentation of atrophy, white matter, gray matter or CSF. over all probabilities in the  ... 
doi:10.1007/978-3-540-39899-8_75 fatcat:hwefcy6q5vc67c3ttdktjoexny

Brain Mri Segmentation And Lesions Detection By Em Algorithm

Mounira Rouaïnia, Mohamed Salah Medjram, Noureddine Doghmane
2008 Zenodo  
Then we detect signal abnormalities (MS lesions) as a rejection class containing voxels that are not explained by the built model.  ...  We validate the method on MR images of Multiple Sclerosis patients by comparing its results with those of human expert segmentation.  ...  By the use of a digital brain atlas that contains spatially varying prior probabilities for grey matter (GM), white matter (WM) and cerebro-spinal fluid (CSF), the method can be fully automated.  ... 
doi:10.5281/zenodo.1328951 fatcat:2f6b3jb4eveozelp7vpti7yrsy

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  
MS lesions are detected as voxels that are not well explained by the model.  ...  This paper describes a fully automated model-based method for segmentation of MS lesions from multi-channel MR images.  ...  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

MIMoSA: A Method for Inter-Modal Segmentation Analysis [article]

Alessandra Valcarcel, Kristin Linn, Simon Vandekar, Theodore Satterthwaite, Peter Calabresi, Dzung Pham, Russell Shinohara
2017 bioRxiv   pre-print
Magnetic resonance imaging (MRI) is crucial for in vivo detection and characterization of white matter lesions (WML) in multiple sclerosis.  ...  any voxel is part of a lesion.  ...  Additionally, this project was supported in part by NMSS grant RG-1507-05243.  ... 
doi:10.1101/150284 fatcat:5frtxzrkgvb3npptsdtl6sybee

Fractional Segmentation of White Matter [chapter]

Simon K. Warfield, Carl-Fredrik Westin, Charles R. G. Guttmann, Marilyn Albert, Ferenc A. Jolesz, Ron Kikinis
1999 Lecture Notes in Computer Science  
present at each voxel of the white matter.  ...  We investigated the ability to characterize these different subject groups based upon tissue volumes determined by spatially varying classification, and by the fractional segmentation of the white matter  ...  Acknowledgements This investigation was supported (in part) by a grant from the National Multiple Sclerosis Society (SW) and by NIH grants P41 RR13218-01, R01 RR11747-01A, P01 CA67165-03 and P01 AG04953  ... 
doi:10.1007/10704282_7 fatcat:xqvv2wnoinhkjgfoilylrtkknm

Automated Integration of Multimodal MRI for the Probabilistic Detection of the Central Vein Sign in White Matter Lesions

J.D. Dworkin, P. Sati, A. Solomon, D.L. Pham, R. Watts, M.L. Martin, D. Ontaneda, M.K. Schindler, D.S. Reich, R.T. Shinohara
2018 American Journal of Neuroradiology  
In this study, we present an automated technique for the detection of the central vein sign in white matter lesions.  ...  CONCLUSIONS: The current study presents the first fully automated method for detecting the central vein sign in white matter lesions and demonstrates promising performance in a sample of patients with  ...  performance of a fully automated method for detecting CVS in white matter lesions.  ... 
doi:10.3174/ajnr.a5765 pmid:30213803 pmcid:PMC6177309 fatcat:plqin7fdb5fmfhitrug673nm7e

White matter lesion segmentation using machine learning and weakly labeled MR images

Yuchen Xie, Xiaodong Tao, Benoit M. Dawant, David R. Haynor
2011 Medical Imaging 2011: Image Processing  
The lesion segmentation in 3D is done by using the probability distributions to generate a confidence map of lesion and applying a graph based segmentation algorithm to label lesion voxels.  ...  We propose a fast, learning-based algorithm for segmenting white matter (WM) lesions for magnetic resonance (MR) brain images. The inputs to the algorithm are T1, T2, and FLAIR images.  ...  Therefore, based on this initial lesion segmentation in 3D, we recompute the histograms and re-estimate the probability distribution of lesion voxels for each channel.  ... 
doi:10.1117/12.878237 dblp:conf/miip/XieT11 fatcat:xx2dkza7brgczmdrutjjuactdq

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).  ...  The new algorithm uses a combination of intensity, anatomical, and morphological probability maps.  ...  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

Semi-automated Robust Quantification of Lesions (SRQL) Toolbox

Kaori Ito, Julia Anglin, Sook-Lei Liew
2017 Research Ideas and Outcomes  
correction that removes healthy white matter voxels from the lesion mask, thereby making lesions slightly more robust to subjective errors; 2) an automated report of descriptive statistics on lesions  ...  We developed the Semi-automated Robust Quantification of Lesions (SRQL;; DOI: 10.5281/zenodo.267213) Toolbox that performs several analysis steps: 1) a white matter intensity  ...  White Matter Intensity Correction A semi-automated white matter intensity correction was implemented to remove healthy white matter voxels that may have accidentally been included in manual lesion segmentations  ... 
doi:10.3897/rio.3.e12259 fatcat:rdpk6etqsne3jocg4rvqmqlh3m

Tractography in the presence of white matter lesions in multiple sclerosis [article]

Ilona Lipp, Greg D Parker, Emma Tallantyre, Alex Goodall, Steluta Grama, Eleonora Patitucci, Phoebe Heveron, Valentina Tomassini, Derek Jones
2019 bioRxiv   pre-print
Our results show that MS white matter lesions impact fibre orientation reconstructions but this does not appear to hinder the ability to anatomically localise white matter tracts in MS.  ...  Diffusion MRI-based tractography is being used increasingly to segment white matter tracts as regions-of-interest for subsequent quantitative analysis.  ...  The study was funded by a research grant of the MS Society UK. DKJ is supported by a Wellcome Trust Investigator Award (096646/Z/11/Z) and a Wellcome Trust Strategic Award (104943/Z/14/Z).  ... 
doi:10.1101/559708 fatcat:wxoapenumzgixkhbyy3gdi2apq

Fuzzy Multi-channel Clustering with Individualized Spatial Priors for Segmenting Brain Lesions and Infarcts [chapter]

Evangelia I. Zacharaki, Guray Erus, Anastasios Bezerianos, Christos Davatzikos
2012 IFIP Advances in Information and Communication Technology  
These priors are calculated by estimating the statistical voxel-wise variation of the healthy anatomy, and identifying abnormalities as deviations from normality.  ...  The method combines intensity based fuzzy c-means (FCM) segmentation with spatial probability maps calculated from a normative set of images from healthy individuals.  ...  This research was supported by a Marie Curie International Reintegration Grant within the 7 th European Community Framework Programme.  ... 
doi:10.1007/978-3-642-33412-2_8 fatcat:mj26attc5bhotjs6v2xfakjxly

An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis

Paul Schmidt, Christian Gaser, Milan Arsic, Dorothea Buck, Annette Förschler, Achim Berthele, Muna Hoshi, Rüdiger Ilg, Volker J. Schmid, Claus Zimmer, Bernhard Hemmer, Mark Mühlau
2012 NeuroImage  
and validation of an automated 75 algorithm for segmentation of T2-hyperintense WM lesions in MS 76 based on a T2-weighted fluid-attenuated (FLAIR) and a three-NeuroImage xxx (2011) xxx-xxx ⁎  ...  Therefore, in the vast majority of clinical trials, lesions were 72 traced manually slice by slicesometimes with the help of semi-73 automated tools for contour detection. 74 Here, we aimed at the development  ...  toward a liberal assumption by voxel-wise 434 weighing the likelihood of belonging to gray or white matter against 435 the likelihood of belonging to lesions.  ... 
doi:10.1016/j.neuroimage.2011.11.032 pmid:22119648 fatcat:ibdycqqfcrhrjembydz6kw573y

An Improved Algorithm of White Matter Hyperintensity Detection in Elderly Adults

T Ding, AD Cohen, EE O'Connor, HT Karim, A Crainiceanu, J Muschelli, O Lopez, WE Klunk, HJ Aizenstein, R Krafty, CM Crainiceanu, DL Tudorascu
2019 NeuroImage: Clinical  
Automated segmentation of the aging brain raises significant challenges because of the prevalence, extent, and heterogeneity of white matter hyperintensities.  ...  OASIS-AD is a major refinement of OASIS that takes into account the specific challenges raised by white matter hyperintensities in Alzheimer's disease.  ...  Acknowledgement This work was supported by the following National Institutes of Health/NIA grants: R01 AG063752, P30 AG066468, RF1 AG025516, P01 AG025204, R01 AG034852, R01 GM113243.  ... 
doi:10.1016/j.nicl.2019.102151 pmid:31927502 pmcid:PMC6957792 fatcat:2pqe3mbl4vaxxkuygxmuuwumwa

An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus

2010 Frontiers in Human Neuroscience  
The gold standard lesion segmentation was created via manual tracing of white matter lesions performed by an experienced rater.  ...  , multi-level method to segment white matter brain lesions and apply it to lupus.  ... 
doi:10.3389/fnhum.2010.00027 pmid:20428508 pmcid:PMC2859868 fatcat:66a2655px5bq3ark65zpzaqp2u

Automated model-based tissue classification of MR images of the brain

K. Van Leemput, F. Maes, D. Vandermeulen, P. Suetens
1999 IEEE Transactions on Medical Imaging  
The algorithm is able to segment single-and multispectral MR images, corrects for MR signal inhomogeneities, and incorporates contextual information by means of Markov random Fields (MRF's).  ...  This makes the method fully automated and therefore it provides objective and reproducible segmentations. We have validated the technique on simulated as well as on real MR images of the brain.  ...  We impose that a voxel surrounded by white-matter and gray-matter voxels must have the same probability to be white matter as to be gray matter.  ... 
doi:10.1109/42.811270 pmid:10628949 fatcat:5vsizlvwenhqxe7qfsnwzea43q
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