Multimodal brain image analysis : first international workshop, MBIA 2011, held in conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011 : proceedings最新文献

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Identifying Neuroimaging and Proteomic Biomarkers for MCI and AD via the Elastic Net 通过弹性网络识别MCI和AD的神经影像学和蛋白质组学生物标志物
Li Shen, Sungeun Kim, Y. Qi, M. Inlow, S. Swaminathan, K. Nho, Jing Wan, S. Risacher, L. Shaw, J. Trojanowski, M. Weiner, A. Saykin
{"title":"Identifying Neuroimaging and Proteomic Biomarkers for MCI and AD via the Elastic Net","authors":"Li Shen, Sungeun Kim, Y. Qi, M. Inlow, S. Swaminathan, K. Nho, Jing Wan, S. Risacher, L. Shaw, J. Trojanowski, M. Weiner, A. Saykin","doi":"10.1007/978-3-642-24446-9_4","DOIUrl":"https://doi.org/10.1007/978-3-642-24446-9_4","url":null,"abstract":"","PeriodicalId":90657,"journal":{"name":"Multimodal brain image analysis : first international workshop, MBIA 2011, held in conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011 : proceedings","volume":"103 1","pages":"27-34"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78085020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 57
Heritability of White Matter Fiber Tract Shapes: A HARDI Study of 198 Twins. 198对双胞胎白质纤维束形状的遗传力。
Yan Jin, Yonggang Shi, Shantanu H Joshi, Neda Jahanshad, Liang Zhan, Greig I de Zubicaray, Katie L McMahon, Nicholas G Martin, Margaret J Wright, Arthur W Toga, Paul M Thompson
{"title":"Heritability of White Matter Fiber Tract Shapes: A HARDI Study of 198 Twins.","authors":"Yan Jin,&nbsp;Yonggang Shi,&nbsp;Shantanu H Joshi,&nbsp;Neda Jahanshad,&nbsp;Liang Zhan,&nbsp;Greig I de Zubicaray,&nbsp;Katie L McMahon,&nbsp;Nicholas G Martin,&nbsp;Margaret J Wright,&nbsp;Arthur W Toga,&nbsp;Paul M Thompson","doi":"10.1007/978-3-642-24446-9_5","DOIUrl":"https://doi.org/10.1007/978-3-642-24446-9_5","url":null,"abstract":"<p><p>Genetic analysis of diffusion tensor images (DTI) shows great promise in revealing specific genetic variants that affect brain integrity and connectivity. Most genetic studies of DTI analyze voxel-based diffusivity indices in the image space (such as 3D maps of fractional anisotropy) and overlook tract geometry. Here we propose an automated workflow to cluster fibers using a white matter probabilistic atlas and perform genetic analysis on the shape characteristics of fiber tracts. We apply our approach to large study of 4-Tesla high angular resolution diffusion imaging (HARDI) data from 198 healthy, young adult twins (age: 20-30). Illustrative results show heritability for the shapes of several major tracts, as color-coded maps.</p>","PeriodicalId":90657,"journal":{"name":"Multimodal brain image analysis : first international workshop, MBIA 2011, held in conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011 : proceedings","volume":"2011 ","pages":"35-43"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4205954/pdf/nihms393571.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32772939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 17
Accounting for Random Regressors: A Unified Approach to Multi-modality Imaging. 考虑随机回归量:多模态成像的统一方法。
Xue Yang, Carolyn B Lauzon, Ciprian Crainiceanu, Brian Caffo, Susan M Resnick, Bennett A Landman
{"title":"Accounting for Random Regressors: A Unified Approach to Multi-modality Imaging.","authors":"Xue Yang,&nbsp;Carolyn B Lauzon,&nbsp;Ciprian Crainiceanu,&nbsp;Brian Caffo,&nbsp;Susan M Resnick,&nbsp;Bennett A Landman","doi":"10.1007/978-3-642-24446-9_1","DOIUrl":"https://doi.org/10.1007/978-3-642-24446-9_1","url":null,"abstract":"<p><p>Massively univariate regression and inference in the form of statistical parametric mapping have transformed the way in which multi-dimensional imaging data are studied. In functional and structural neuroimaging, the <i>de facto</i> standard \"design matrix\"-based general linear regression model and its multi-level cousins have enabled investigation of the biological basis of the human brain. With modern study designs, it is possible to acquire multiple three-dimensional assessments of the same individuals - e.g., structural, functional and quantitative magnetic resonance imaging alongside functional and ligand binding maps with positron emission tomography. Current statistical methods assume that the regressors are non-random. For more realistic multi-parametric assessment (e.g., voxel-wise modeling), distributional consideration of all observations is appropriate (e.g., Model II regression). Herein, we describe a unified regression and inference approach using the design matrix paradigm which accounts for both random and non-random imaging regressors.</p>","PeriodicalId":90657,"journal":{"name":"Multimodal brain image analysis : first international workshop, MBIA 2011, held in conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011 : proceedings","volume":"7012 ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-3-642-24446-9_1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32773945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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