Bayesian and grAphical models for biomedical imaging : first International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014 ; revised selected papers. BAMBI (Workshop) (1st : 2014 : Cambridge, Mass.)最新文献

筛选
英文 中文
Spherical Topic Models for Imaging Phenotype Discovery in Genetic Studies. 在遗传研究中发现成像表型的球形主题模型
Kayhan N Batmanghelich, Michael Cho, Raul San Jose, Polina Golland
{"title":"Spherical Topic Models for Imaging Phenotype Discovery in Genetic Studies.","authors":"Kayhan N Batmanghelich, Michael Cho, Raul San Jose, Polina Golland","doi":"10.1007/978-3-319-12289-2_10","DOIUrl":"10.1007/978-3-319-12289-2_10","url":null,"abstract":"<p><p>In this paper, we use Spherical Topic Models to discover the latent structure of lung disease. This method can be widely employed when a measurement for each subject is provided as a normalized histogram of relevant features. In this paper, the resulting descriptors are used as phenotypes to identify genetic markers associated with the Chronic Obstructive Pulmonary Disease (COPD). Features extracted from images capture the heterogeneity of the disease and therefore promise to improve detection of relevant genetic variants in Genome Wide Association Studies (GWAS). Our generative model is based on normalized histograms of image intensity of each subject and it can be readily extended to other forms of features as long as they are provided as normalized histograms. The resulting algorithm represents the intensity distribution as a combination of meaningful latent factors and mixing co-efficients that can be used for genetic association analysis. This approach is motivated by a clinical hypothesis that COPD symptoms are caused by multiple coexisting disease processes. Our experiments show that the new features enhance the previously detected signal on chromosome 15 with respect to standard respiratory and imaging measurements.</p>","PeriodicalId":90796,"journal":{"name":"Bayesian and grAphical models for biomedical imaging : first International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014 ; revised selected papers. BAMBI (Workshop) (1st : 2014 : Cambridge, Mass.)","volume":"8677 ","pages":"107-117"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4337963/pdf/nihms637936.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33415065","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: 0
A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Weighted Imaging. 用贝叶斯方法从有限扩散加权成像中识别舌间指肌。
Chuyang Ye, Aaron Carass, Emi Murano, Maureen Stone, Jerry L Prince
{"title":"A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Weighted Imaging.","authors":"Chuyang Ye,&nbsp;Aaron Carass,&nbsp;Emi Murano,&nbsp;Maureen Stone,&nbsp;Jerry L Prince","doi":"10.1007/978-3-319-12289-2_2","DOIUrl":"https://doi.org/10.1007/978-3-319-12289-2_2","url":null,"abstract":"<p><p>Fiber tracking in crossing regions is a well known issue in diffusion tensor imaging (DTI). Multi-tensor models have been proposed to cope with the issue. However, in cases where only a limited number of gradient directions can be acquired, for example in the tongue, the multi-tensor models fail to resolve the crossing correctly due to insufficient information. In this work, we address this challenge by using a fixed tensor basis and incorporating prior directional knowledge. Within a maximum a posteriori (MAP) framework, sparsity of the basis and prior directional knowledge are incorporated in the prior distribution, and data fidelity is encoded in the likelihood term. An objective function can then be obtained and solved using a noise-aware weighted <i>ℓ</i><sub>1</sub>-norm minimization. Experiments on a digital phantom and <i>in vivo</i> tongue diffusion data demonstrate that the proposed method is able to resolve crossing fibers with limited gradient directions.</p>","PeriodicalId":90796,"journal":{"name":"Bayesian and grAphical models for biomedical imaging : first International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014 ; revised selected papers. BAMBI (Workshop) (1st : 2014 : Cambridge, Mass.)","volume":"8677 ","pages":"13-24"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-3-319-12289-2_2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33003519","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: 6
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信