{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T12:36:21Z","timestamp":1772886981292,"version":"3.50.1"},"reference-count":70,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2020,1,14]],"date-time":"2020-01-14T00:00:00Z","timestamp":1578960000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["NeuroImage"],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1016\/j.neuroimage.2019.116327","type":"journal-article","created":{"date-parts":[[2019,11,3]],"date-time":"2019-11-03T00:29:00Z","timestamp":1572740940000},"page":"116327","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":69,"special_numbering":"C","title":["White matter hyperintensities and their relationship to cognition: Effects of segmentation algorithm"],"prefix":"10.1016","volume":"206","author":[{"given":"Meral A.","family":"Tubi","sequence":"first","affiliation":[]},{"given":"Franklin W.","family":"Feingold","sequence":"additional","affiliation":[]},{"given":"Deydeep","family":"Kothapalli","sequence":"additional","affiliation":[]},{"given":"Evan T.","family":"Hare","sequence":"additional","affiliation":[]},{"given":"Kevin S.","family":"King","sequence":"additional","affiliation":[]},{"given":"Paul M.","family":"Thompson","sequence":"additional","affiliation":[]},{"given":"Meredith N.","family":"Braskie","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.neuroimage.2019.116327_bib1","article-title":"The effect of midlife cardiovascular risk factors on white matter hyperintensity volume and cognition two decades later in normal ageing women","author":"Aljondi","year":"2018","journal-title":"Brain Imag. Behav."},{"key":"10.1016\/j.neuroimage.2019.116327_bib2","doi-asserted-by":"crossref","first-page":"2880","DOI":"10.1016\/j.neuropsychologia.2012.08.011","article-title":"Participantive cognitive complaints and amyloid burden in cognitively normal older individuals","volume":"50","author":"Amariglio","year":"2012","journal-title":"Neuropsychologia"},{"key":"10.1016\/j.neuroimage.2019.116327_bib3","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1001\/archneur.63.2.246","article-title":"Association of white matter hyperintensity volume with decreased cognitive functioning: the Framingham Heart Study","volume":"63","author":"Au","year":"2006","journal-title":"Arch. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib4","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.media.2007.06.004","article-title":"Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain","volume":"12","author":"Avants","year":"2008","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.neuroimage.2019.116327_bib5","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1017\/S1355617706061078","article-title":"Role of frontal versus temporal cortex in verbal fluency as revealed by voxel-based lesion symptom mapping","volume":"12","author":"Baldo","year":"2006","journal-title":"J.\u00a0Int. Neuropsychol. Soc."},{"key":"10.1016\/j.neuroimage.2019.116327_bib6","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1186\/1471-2377-12-126","article-title":"The association between cognitive function and white matter lesion location in older adults: a systematic review","volume":"12","author":"Bolandzadeh","year":"2012","journal-title":"BMC Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib7","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1002\/acn3.343","article-title":"White matter hyperintensities, incident mild cognitive impairment, and cognitive decline in old age","volume":"3","author":"Boyle","year":"2016","journal-title":"Ann. Clin. Transl. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib8","doi-asserted-by":"crossref","first-page":"1669","DOI":"10.1016\/j.neurobiolaging.2008.09.012","article-title":"Plaque and tangle imaging and cognition in normal aging and Alzheimer\u2019s disease","volume":"31","author":"Braskie","year":"2010","journal-title":"Neurobiol. Aging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib9","doi-asserted-by":"crossref","first-page":"181","DOI":"10.31887\/DCNS.2009.11.2\/ambrickman","article-title":"Structural neuroimaging in Alzheimer\u2019s disease: do white matter hyperintensities matter?","volume":"11","author":"Brickman","year":"2009","journal-title":"Dialogues Clin. Neurosci."},{"key":"10.1016\/j.neuroimage.2019.116327_bib10","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1016\/j.neuroimage.2004.06.018","article-title":"A\u00a0unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume","volume":"23","author":"Buckner","year":"2004","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroimage.2019.116327_bib11","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s12021-015-9260-y","article-title":"Automatic detection of white matter hyperintensities in healthy aging and pathology using magnetic resonance imaging: a review","volume":"13","author":"Caligiuri","year":"2015","journal-title":"Neuroinformatics"},{"key":"10.1016\/j.neuroimage.2019.116327_bib12","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1007\/s11682-012-9186-z","article-title":"Development and assessment of a composite score for memory in the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI)","volume":"6","author":"Crane","year":"2012","journal-title":"Brain Imag. Behav."},{"key":"10.1016\/j.neuroimage.2019.116327_bib13","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.neuroimage.2017.06.009","article-title":"Performance comparison of 10 different classification techniques in segmenting white matter hyperintensities in aging","volume":"157","author":"Dadar","year":"2017","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroimage.2019.116327_bib14","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1002\/1531-8249(200002)47:2<145::AID-ANA3>3.0.CO;2-P","article-title":"Cerebral white matter lesions and cognitive function: the Rotterdam Scan Study","volume":"47","author":"de Groot","year":"2000","journal-title":"Ann. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib15","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1002\/ana.22062","article-title":"Visceral fat is associated with\u00a0lower brain volume in healthy middle-aged adults","volume":"68","author":"Debette","year":"2010","journal-title":"Ann. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib16","doi-asserted-by":"crossref","first-page":"2077","DOI":"10.1212\/WNL.45.11.2077","article-title":"The effect of white matter hyperintensity volume on brain structure, cognitive performance, and cerebral metabolism of glucose in 51 healthy adults","volume":"45","author":"DeCarli","year":"1995","journal-title":"Neurology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib17","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1097\/00019442-200411000-00006","article-title":"A\u00a0volumetric study of MRI signal hyperintensities in late-life depression","volume":"12","author":"Firbank","year":"2004","journal-title":"Am. J. Geriatr. Psychiatry"},{"key":"10.1016\/j.neuroimage.2019.116327_bib18","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/S0896-6273(02)00569-X","article-title":"Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain","volume":"33","author":"Fischl","year":"2002","journal-title":"Neuron"},{"key":"10.1016\/j.neuroimage.2019.116327_bib19","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1038\/ncpneuro0638","article-title":"The effect of white matter lesions\u00a0on cognition in the elderly--small but detectable","volume":"3","author":"Frisoni","year":"2007","journal-title":"Nat. Clin. Pract. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib20","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1007\/s11682-012-9176-1","article-title":"A\u00a0composite score for executive functioning, validated in Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment","volume":"6","author":"Gibbons","year":"2012","journal-title":"Brain Imag. Behav."},{"key":"10.1016\/j.neuroimage.2019.116327_bib21","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.1002\/jmri.22004","article-title":"Automatic segmentation of white matter hyperintensities in the elderly using FLAIR images at 3T","volume":"31","author":"Gibson","year":"2010","journal-title":"J.\u00a0Magn. Reson. Imaging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib22","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1159\/000079199","article-title":"Regional distribution of white matter hyperintensities in vascular dementia, Alzheimer\u2019s disease and healthy aging","volume":"18","author":"Gootjes","year":"2004","journal-title":"Dement. Geriatr. Cognit. Disord."},{"key":"10.1016\/j.neuroimage.2019.116327_bib23","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.nicl.2015.04.017","article-title":"The effects of white matter hyperintensities and amyloid deposition on Alzheimer dementia","volume":"8","author":"Gordon","year":"2015","journal-title":"Neuroimage Clin."},{"key":"10.1016\/j.neuroimage.2019.116327_bib24","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.neuroimage.2016.07.018","article-title":"BIANCA (Brain Intensity AbNormality Classification Algorithm): a new tool for automated segmentation of white matter hyperintensities","volume":"141","author":"Griffanti","year":"2016","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroimage.2019.116327_bib25","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.neuroimage.2017.03.024","article-title":"Classification and characterization of periventricular and deep white matter hyperintensities on MRI: a study in older adults","volume":"170","author":"Griffanti","year":"2018","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroimage.2019.116327_bib26","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/0730-725X(96)00018-5","article-title":"Quantification of MRI lesion load in multiple sclerosis: a comparison of three computer-assisted techniques","volume":"14","author":"Grimaud","year":"1996","journal-title":"Magn. Reson. Imaging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib27","doi-asserted-by":"crossref","first-page":"2766","DOI":"10.1016\/j.neurobiolaging.2012.01.016","article-title":"White matter hyperintensities predict amyloid increase in Alzheimer\u2019s disease","volume":"33","author":"Grimmer","year":"2012","journal-title":"Neurobiol. Aging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib28","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1037\/0894-4105.14.2.224","article-title":"The cognitive correlates of white matter abnormalities in normal aging: a quantitative review","volume":"14","author":"Gunning-Dixon","year":"2000","journal-title":"Neuropsychology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib29","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/2051-5960-1-14","article-title":"Do brain T2\/FLAIR white matter hyperintensities correspond to myelin loss in normal aging? A radiologic-neuropathologic correlation study","volume":"1","author":"Haller","year":"2013","journal-title":"Acta Neuropathol. Commun."},{"key":"10.1016\/j.neuroimage.2019.116327_bib30","doi-asserted-by":"crossref","first-page":"645","DOI":"10.3233\/JAD-160907","article-title":"Recent progress in Alzheimer\u2019s disease Research, Part 3: diagnosis and treatment","volume":"57","author":"Hane","year":"2017","journal-title":"J.\u00a0Alzheimer\u2019s Dis."},{"key":"10.1016\/j.neuroimage.2019.116327_bib31","doi-asserted-by":"crossref","first-page":"16233","DOI":"10.1523\/JNEUROSCI.2462-12.2012","article-title":"Cognitive profile of amyloid burden and white matter hyperintensities in cognitively normal older adults","volume":"32","author":"Hedden","year":"2012","journal-title":"J.\u00a0Neurosci."},{"key":"10.1016\/j.neuroimage.2019.116327_bib32","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1007\/s00234-016-1648-3","article-title":"On the computational assessment of white matter hyperintensity progression: difficulties in method selection and bias field correction performance on images with significant white matter pathology","volume":"58","author":"Hernandez","year":"2016","journal-title":"Neuroradiology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib33","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1017\/S135561771800022X","article-title":"Neuropsychological profiles and trajectories in preclinical Alzheimer\u2019s disease","volume":"24","author":"Ho","year":"2018","journal-title":"J.\u00a0Int. Neuropsychol. Soc."},{"key":"10.1016\/j.neuroimage.2019.116327_bib34","doi-asserted-by":"crossref","first-page":"76","DOI":"10.3389\/fnagi.2013.00076","article-title":"White matter hyperintensities segmentation: a new semi-automated method","volume":"5","author":"Iorio","year":"2013","journal-title":"Front. Aging Neurosci."},{"key":"10.1016\/j.neuroimage.2019.116327_bib35","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/S1361-8415(01)00036-6","article-title":"A\u00a0global optimisation method for robust affine registration of brain images","volume":"5","author":"Jenkinson","year":"2001","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.neuroimage.2019.116327_bib36","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1006\/nimg.2002.1132","article-title":"Improved optimization for the robust and accurate linear registration and motion correction of brain images","volume":"17","author":"Jenkinson","year":"2002","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroimage.2019.116327_bib37","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1161\/01.STR.0000049766.26453.E9","article-title":"Visual rating of age-related white matter changes on magnetic resonance imaging: scale comparison, interrater agreement, and correlations with quantitative measurements","volume":"34","author":"Kapeller","year":"2003","journal-title":"Stroke"},{"key":"10.1016\/j.neuroimage.2019.116327_bib38","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.biopsych.2008.03.024","article-title":"Classification of white matter lesions on magnetic resonance imaging in elderly persons","volume":"64","author":"Kim","year":"2008","journal-title":"Biol. Psychiatry"},{"key":"10.1016\/j.neuroimage.2019.116327_bib39","doi-asserted-by":"crossref","first-page":"2127","DOI":"10.1212\/WNL.0000000000000505","article-title":"Presence and progression of white matter hyperintensities and cognition: a meta-analysis","volume":"82","author":"Kloppenborg","year":"2014","journal-title":"Neurology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib40","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1177\/0271678X17740501","article-title":"Lesion location matters: the relationships between white matter hyperintensities on cognition in the healthy elderly","volume":"39","author":"Lampe","year":"2017","journal-title":"J.\u00a0Cereb. Blood Flow Metab."},{"key":"10.1016\/j.neuroimage.2019.116327_bib41","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.1161\/01.STR.28.8.1614","article-title":"Variable agreement between visual rating scales for white matter hyperintensities on MRI. Comparison of 13 rating scales in a poststroke cohort","volume":"28","author":"Mantyla","year":"1997","journal-title":"Stroke"},{"key":"10.1016\/j.neuroimage.2019.116327_bib42","doi-asserted-by":"crossref","first-page":"939","DOI":"10.1212\/WNL.34.7.939","article-title":"Clinical diagnosis of Alzheimer\u2019s disease","volume":"34","author":"McKhann","year":"1984","journal-title":"Neurology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib43","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1016\/j.jalz.2016.06.2365","article-title":"Detecting cognitive changes in preclinical Alzheimer\u2019s disease: a review of its feasibility","volume":"13","author":"Mortamais","year":"2017","journal-title":"Alzheimers Dement"},{"key":"10.1016\/j.neuroimage.2019.116327_bib44","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1098\/rspb.1996.0146","article-title":"Generating \u2019tiger\u2019 as an animal name or a word beginning with T: differences in brain activation","volume":"263","author":"Mummery","year":"1996","journal-title":"Proc. Biol. Sci."},{"key":"10.1016\/j.neuroimage.2019.116327_bib45","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1001\/archneurol.2010.280","article-title":"Functional impact of white matter hyperintensities in cognitively normal elderly participants","volume":"67","author":"Murray","year":"2010","journal-title":"Arch. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib46","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.neuropsychologia.2016.09.024","article-title":"Category and design fluency in mild cognitive impairment: performance, strategy use, and neural correlates","volume":"93","author":"Peter","year":"2016","journal-title":"Neuropsychologia"},{"key":"10.1016\/j.neuroimage.2019.116327_bib47","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1038\/nrneurol.2015.10","article-title":"White matter hyperintensities, cognitive impairment and dementia: an update","volume":"11","author":"Prins","year":"2015","journal-title":"Nat. Rev. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib48","doi-asserted-by":"crossref","first-page":"1533","DOI":"10.1212\/01.WNL.0000123264.40498.B6","article-title":"Measuring progression of cerebral white matter lesions on MRI: visual rating and volumetrics","volume":"62","author":"Prins","year":"2004","journal-title":"Neurology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib49","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1001\/jamaneurol.2013.1321","article-title":"White matter hyperintensities and cerebral amyloidosis: necessary and sufficient for clinical expression of Alzheimer disease?","volume":"70","author":"Provenzano","year":"2013","journal-title":"JAMA Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib71","series-title":"R: A Language and Environment for Statistical Computing","author":"R Core Team","year":"2013"},{"key":"10.1016\/j.neuroimage.2019.116327_bib50","doi-asserted-by":"crossref","first-page":"1154","DOI":"10.1016\/j.jalz.2017.01.026","article-title":"Associations between amyloid beta and white matter hyperintensities: a systematic review","volume":"13","author":"Roseborough","year":"2017","journal-title":"Alzheimers Dement"},{"key":"10.1016\/j.neuroimage.2019.116327_bib51","series-title":"Bayesian Inference for Structured Additive Regression Models for Large-Scale Problems with Applications to Medical Imaging","author":"Schmidt","year":"2017"},{"key":"10.1016\/j.neuroimage.2019.116327_bib52","doi-asserted-by":"crossref","first-page":"3774","DOI":"10.1016\/j.neuroimage.2011.11.032","article-title":"An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis","volume":"59","author":"Schmidt","year":"2012","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroimage.2019.116327_bib53","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.neurobiolaging.2017.12.004","article-title":"Brain amyloid burden and cerebrovascular disease are synergistically associated with neurometabolism in cognitively unimpaired older adults","volume":"63","author":"Schreiner","year":"2018","journal-title":"Neurobiol. Aging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib54","doi-asserted-by":"crossref","first-page":"221","DOI":"10.3389\/fnagi.2015.00221","article-title":"Cerebral amyloid and hypertension are independently associated with white matter lesions in elderly","volume":"7","author":"Scott","year":"2015","journal-title":"Front. Aging Neurosci."},{"key":"10.1016\/j.neuroimage.2019.116327_bib55","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.neurobiolaging.2016.08.014","article-title":"Cerebral amyloid is associated with greater white-matter hyperintensity accrual in cognitively normal older adults","volume":"48","author":"Scott","year":"2016","journal-title":"Neurobiol. Aging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib56","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1002\/ana.21610","article-title":"Cerebrospinal fluid biomarker signature in Alzheimer\u2019s disease neuroimaging initiative participants","volume":"65","author":"Shaw","year":"2009","journal-title":"Ann. Neurol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib57","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1111\/j.1365-2990.2007.00828.x","article-title":"White matter lesions in an unselected cohort of the elderly: astrocytic, microglial and oligodendrocyte precursor cell responses","volume":"33","author":"Simpson","year":"2007","journal-title":"Neuropathol. Appl. Neurobiol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib58","first-page":"391783","article-title":"Validation of automated white matter hyperintensity segmentation","author":"Smart","year":"2011","journal-title":"J.\u00a0Aging Res."},{"key":"10.1016\/j.neuroimage.2019.116327_bib59","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1212\/WNL.0b013e318217e7c8","article-title":"Correlations between MRI white matter lesion location and executive function and episodic memory","volume":"76","author":"Smith","year":"2011","journal-title":"Neurology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib60","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1148\/radiol.2431052111","article-title":"Decline in total cerebral blood flow is linked with increase in periventricular but not deep white matter hyperintensities","volume":"243","author":"ten Dam","year":"2007","journal-title":"Radiology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib61","doi-asserted-by":"crossref","first-page":"1310","DOI":"10.1109\/TMI.2010.2046908","article-title":"N4ITK: improved N3 bias correction","volume":"29","author":"Tustison","year":"2010","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib62","doi-asserted-by":"crossref","first-page":"836","DOI":"10.1161\/01.STR.0000202585.26325.74","article-title":"Impact of white matter hyperintensities scoring method on correlations with clinical data: the LADIS study","volume":"37","author":"van Straaten","year":"2006","journal-title":"Stroke"},{"key":"10.1016\/j.neuroimage.2019.116327_bib63","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s00234-014-1466-4","article-title":"Automatic segmentation and volumetric quantification of white matter hyperintensities on fluid-attenuated inversion recovery images using the extreme value distribution","volume":"57","author":"Wang","year":"2015","journal-title":"Neuroradiology"},{"key":"10.1016\/j.neuroimage.2019.116327_bib64","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1111\/bpa.12219","article-title":"Age-associated white matter lesions: the MRC cognitive function and ageing study","volume":"25","author":"Wharton","year":"2015","journal-title":"Brain Pathol."},{"key":"10.1016\/j.neuroimage.2019.116327_bib65","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/0022-510X(82)90155-1","article-title":"Plaques, tangles and dementia. A quantitative study","volume":"56","author":"Wilcock","year":"1982","journal-title":"J.\u00a0Neurol. Sci."},{"key":"10.1016\/j.neuroimage.2019.116327_bib66","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1002\/hbm.23857","article-title":"Cognitive abilities, brain white matter hyperintensity volume, and structural network connectivity in older age","volume":"39","author":"Wiseman","year":"2018","journal-title":"Hum. Brain Mapp."},{"key":"10.1016\/j.neuroimage.2019.116327_bib67","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/S0378-3758(99)00041-5","article-title":"Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics","volume":"82","author":"Yekutieli","year":"1999","journal-title":"J.\u00a0Stat. Plan. Inference"},{"key":"10.1016\/j.neuroimage.2019.116327_bib68","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1097\/01.rmr.0000245456.98029.a8","article-title":"Current concepts of analysis of cerebral white matter hyperintensities on magnetic resonance imaging","volume":"16","author":"Yoshita","year":"2005","journal-title":"Top. Magn. Reson. Imaging"},{"key":"10.1016\/j.neuroimage.2019.116327_bib69","doi-asserted-by":"crossref","first-page":"2192","DOI":"10.1212\/01.wnl.0000249119.95747.1f","article-title":"Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD","volume":"67","author":"Yoshita","year":"2006","journal-title":"Neurology"}],"container-title":["NeuroImage"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1053811919309188?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1053811919309188?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:23:07Z","timestamp":1760955787000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1053811919309188"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2]]},"references-count":70,"alternative-id":["S1053811919309188"],"URL":"https:\/\/doi.org\/10.1016\/j.neuroimage.2019.116327","relation":{},"ISSN":["1053-8119"],"issn-type":[{"value":"1053-8119","type":"print"}],"subject":[],"published":{"date-parts":[[2020,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"White matter hyperintensities and their relationship to cognition: Effects of segmentation algorithm","name":"articletitle","label":"Article Title"},{"value":"NeuroImage","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neuroimage.2019.116327","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2019 Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"116327"}}