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Automated segmentation of brain lesions by combining intensity and spatial information

Bilwaj Gaonkar, Guray Erus, Nick Bryan, Christos Davatzikos
2010 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
We present a new automated method, that combines intensity based lesion segmentation with a false positive elimination method based on the spatial distribution of lesions.  ...  A lesion probability map that represents the spatial distribution of true and false positives on the intensity based segmentation is constructed using the segmented lesions and manual masks.  ...  In [2] the intensity and the spatial information are combined together in a voxel based feature vector and a kNN classifier is used to segment lesions.  ... 
doi:10.1109/isbi.2010.5490407 dblp:conf/isbi/GaonkarEBD10 fatcat:etv3w5w3xnggtgnunzzfsg5hju

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  
It is based on a k-Nearest Neighbor (KNN) classification technique, which builds a feature space from voxel intensities and spatial information.  ...  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.  ...  Similarity Index Discussion The combination of spatial information and gray values of MR images in KNNclassification provides a strong technique for WML-segmentation with a high accuracy.  ... 
doi:10.1007/978-3-540-39899-8_75 fatcat:hwefcy6q5vc67c3ttdktjoexny

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

E Herskovits, R Bryan, F Yang
2008 Advances in Medical Sciences  
Conclusions: A Bayesian lesion-segmentation algorithm that collects multi-channel signal-intensity and spatial information from MR images of the brain shows potential for accurately segmenting brain lesions  ...  Conclusions: A Bayesian lesion-segmentation algorithm that collects multi-channel signal-intensity and spatial information from MR images of the brain shows potential for accurately segmenting brain lesions  ...  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

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  
The results of the automated method are compared with the lesions delineated by human experts, showing a significant total lesion load correlation and an average overall spatial correspondence similar  ...  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

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

Scully
2010 Frontiers in Human Neuroscience  
Schwarz et al. (2009) used Markov random fields to combine spatial distribution and neighborhood intensities.  ...  Anbeek et al. (2005) employed k - nearest-neighbor to incorporate spatial and intensity information.  ... 
doi:10.3389/fnhum.2010.00027 pmid:20428508 pmcid:PMC2859868 fatcat:66a2655px5bq3ark65zpzaqp2u

Brain Mri Segmentation And Lesions Detection By Em Algorithm

Mounira Rouaïnia, Mohamed Salah Medjram, Noureddine Doghmane
2008 Zenodo  
After the enhancement of images contrast and the brain extraction by mathematical morphology algorithm, we proceed to the brain segmentation.  ...  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 multiple sclerosis lesions by model outlier detection

K. Van Leemput, F. Maes, D. Vandermeulen, A. Colchester, P. Suetens
2001 IEEE Transactions on Medical Imaging  
The method performs intensity-based tissue classification using a stochastic model for normal brain images and simultaneously detects MS lesions as outliers that are not well explained by the model.  ...  The results of the automated method are compared with lesion delineations by human experts, showing a high total lesion load correlation.  ...  With and the number of voxels rated as MS lesion by the automated algorithm after hard classification and by the expert, respectively, and the number of voxels rated as lesion by both the automated method  ... 
doi:10.1109/42.938237 pmid:11513020 fatcat:iuop3j6zabg3vidunaoz4u6gg4

A fully automated pipeline for brain structure segmentation in multiple sclerosis

Sandra González-Villá, Arnau Oliver, Yuankai Huo, Xavier Lladó, Bennett A. Landman
2020 NeuroImage: Clinical  
and label fusion, and combine them with an automated lesion segmentation method of the state of the art.  ...  However, most of these strategies tend to be affected by the abnormal MS lesion intensities, which corrupt the structure segmentation result.  ...  Acknowledgements This work has been supported by "La Fundació la Marató de TV3", and by Retos de Investigación TIN2015-73563-JIN and DPI2017-86696-R.  ... 
doi:10.1016/j.nicl.2020.102306 pmid:32585568 pmcid:PMC7322098 fatcat:neaxqicbrjfehlpmghthgx53ca

Ischemic infarct detection, localization, and segmentation in noncontrast CT human brain scans: review of automated methods

Wieslaw L. Nowinski, Jerzy Walecki, Gabriela Półtorak-Szymczak, Katarzyna Sklinda, Bartosz Mruk
2020 PeerJ  
We provide the state-of-the-art review of methods for automated detection, localization, and/or segmentation of ischemic lesions on NCCT in human brain scans along with their comparison, evaluation, and  ...  Noncontrast Computed Tomography (NCCT) of the brain has been the first-line diagnosis for emergency evaluation of acute stroke, so a rapid and automated detection, localization, and/or segmentation of  ...  A number of various methods have been proposed for automated detection, localization, and/or segmentation of ischemic lesions on NCCT in human brain scans.  ... 
doi:10.7717/peerj.10444 pmid:33391867 pmcid:PMC7759129 fatcat:tm3bw52gtjgh5fvw3i4o3i3zma

A comprehensive approach to the segmentation of multichannel three-dimensional MR brain images in multiple sclerosis

Sushmita Datta, Ponnada A. Narayana
2013 NeuroImage: Clinical  
The results of automatic lesion segmentation were reviewed by the expert.  ...  Classification of MR brain images in the presence of lesions, such as multiple sclerosis (MS), is particularly challenging.  ...  First column: T1; second column: T2; third column: FLAIR; fourth column: segmented; and fifth column: boundaries of the segmented lesions superimposed on FLAIR images.  ... 
doi:10.1016/j.nicl.2012.12.007 pmid:24179773 pmcid:PMC3777770 fatcat:r7kpjavvqjh3jiy3fa3zjkp2um

Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis

H. Vrenken, M. Jenkinson, M. A. Horsfield, M. Battaglini, R. A. van Schijndel, E. Rostrup, J. J. G. Geurts, E. Fisher, A. Zijdenbos, J. Ashburner, D. H. Miller, M. Filippi (+5 others)
2012 Journal of Neurology  
Image artifacts need special attention given their effects on image analysis results. (2) Automated image segmentation methods integrating the assessment of lesion load and atrophy are desirable. (3) A  ...  Based on open issues in the field of MS research, and the current state of the art in magnetic resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations  ...  An intensity-based approach to the detection of change in lesions over time could exploit a combination of registration and subtraction as used by Moraal et al. [32, 79, 80] .  ... 
doi:10.1007/s00415-012-6762-5 pmid:23263472 pmcid:PMC3824277 fatcat:s727aflyjrcrpip7d3nuissbhq

Automatic Detection of White Matter Hyperintensities in Healthy Aging and Pathology Using Magnetic Resonance Imaging: A Review

Maria Eugenia Caligiuri, Paolo Perrotta, Antonio Augimeri, Federico Rocca, Aldo Quattrone, Andrea Cherubini
2015 Neuroinformatics  
on multimodal, complementary data, take into account spatial information about the lesions and correct for false positives.  ...  In this paper, we review and compare the large number of automated approaches proposed for segmentation of WMH in the elderly and in patients with vascular risk factors.  ...  Acknowledgments Financial Disclosures/Conflict of interest concerning the research related to the manuscript and the previous 12 months: The authors have no conflict of interest to disclose.  ... 
doi:10.1007/s12021-015-9260-y pmid:25649877 pmcid:PMC4468799 fatcat:ce7pdxj5qrepdldsf6gpf6zdyy

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  
The method combines intensity based fuzzy c-means (FCM) segmentation with spatial probability maps calculated from a normative set of images from healthy individuals.  ...  Quantitative analysis of brain lesions and ischemic infarcts is becoming very important due to their association with cardiovascular disease and normal aging.  ...  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

Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort

Alexandra de Sitter, the MAGNIMS Study Group, Tom Verhoeven, Jessica Burggraaff, Yaou Liu, Jorge Simoes, Serena Ruggieri, Miklos Palotai, Iman Brouwer, Adriaan Versteeg, Viktor Wottschel, Stefan Ropele (+14 others)
2020 Journal of Neurology  
For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations.  ...  MS pathology may deteriorate the performance of automated segmentation methods.  ...  agreement with manual segmentations created by combining manual outlines of three trained raters by majority voting.  ... 
doi:10.1007/s00415-020-10023-1 pmid:32621103 fatcat:l6yvsrfywzbz3agktqfts4byba

Manual, semi-automated, and automated delineation of chronic brain lesions: A comparison of methods

Marko Wilke, Bianca de Haan, Hendrik Juenger, Hans-Otto Karnath
2011 NeuroImage  
The exact delineation of chronic brain lesions is a crucial step when investigating the relationship between brain structure and (dys-)function.  ...  In order to assess the possible contributions from other methods, we compared manual tracing of lesion boundaries with a newly developed semi-automated and a fully automated approach for lesion definition  ...  This work has been supported by the Deutsche Forschungsgemeinschaft DFG (WI3630/1-1, to MW, and KA1258/10-1, to HOK) as well as the Bundesministerium für Bildung und Forschung (BMBF-Verbund 01GW0641 "Räumliche  ... 
doi:10.1016/j.neuroimage.2011.04.014 pmid:21513805 fatcat:s52kee2upvf73lr4dgm7j44yne
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