2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro最新文献_第10页

FMRI brain activity and underlying hemodynamics estimation in a new Bayesian framework 新的贝叶斯框架下的FMRI脑活动和潜在血流动力学估计

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541231

D. Afonso, J. Sanches, M. Lauterbach

{"title":"FMRI brain activity and underlying hemodynamics estimation in a new Bayesian framework","authors":"D. Afonso, J. Sanches, M. Lauterbach","doi":"10.1109/ISBI.2008.4541231","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541231","url":null,"abstract":"The emerging functional MRI (magnetic resonance imaging), fMRI, imaging modality was developed to obtain non-invasive information regarding the neural processes behind pre-determined task. The data is gathered in such a way that the extraction certainty of the desired information is maximized. Still this is a difficult task due to low Signal-to-Noise Ratio (SNR), corrupting noise and artifacts from several sources. The most prevalent method, here called SPM-GLM uses a conventional statistical inference methodology based on the t-statistics, where it assumes a rather rigid shape on the BOLD hemodynamic response function (HRF), constant for the whole region of interest (ROI). A new algorithm, designed in a Bayesian framework, is presented in this paper, called SPM-MAP. The algorithm jointly detects the brain activated regions and the underlying HRF in an adaptative and local basis. This approach presents two main advantages: (1) the activity detection benefits from the method's high flexibility toward the HRF shape; (2) it provides local estimations for the HRF. The SPM-MAP algorithm is validated by using Monte Carlo tests with synthetic data and comparisons with the SPM-GLM are also performed. Tests using real data are also performed and results are compared with the ones provided by the SPM-GLM method tuned by the medical doctor.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"65 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129600628","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: 0

Application and validation of registration framework for real-time atlas guided biopsy 实时图谱引导活检配准框架的应用与验证

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541211

R. Narayanan, D. Shen, C. Davatzikos, E. Crawford, A. Barqawi, P. Werahera, D. Kumar, J. Suri

引用次数: 0

Automation of the detection of lung cancer cells in minimal samples of bronchioalveolar lavage 支气管肺泡灌洗微量标本中肺癌细胞检测的自动化

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4540995

C. Ortíz-de-Solórzano, T. Pengo, Miguel Galarraga, A. Muñoz-Barrutia

引用次数: 1

Sparse representations for limited data tomography 有限数据断层扫描的稀疏表示

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541261

H. Liao, G. Sapiro

引用次数: 64

Image-based simulation of brain arteriovenous malformation hemodynamics 基于图像的脑动静脉畸形血流动力学模拟

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541086

P. Orlowski, J. Noble, Y. Ventikos, J. Byrne, P. Summers

引用次数: 4

A non-linear registration method for DCE-MRI and DCE-CT comparison in bladder tumors 膀胱肿瘤DCE-MRI与DCE-CT比较的非线性配准方法

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541191

K. Passera, L. Mainardi, D. McGrath, J. Naish, D. Buckley, S. Cheung, Y. Watson, A. Caunce, G. Buonaccorsi, J. Logue, Marcus B. Taylor, C. Taylor, J. Waterton, H. Young, G. Parker

引用次数: 7

Triangulating cortical functional networks with anatomical landmarks 用解剖标志对皮质功能网络进行三角剖分

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541070

A. Tucholka, B. Thirion, P. Pinel, J. Poline, J. F. Mangin

引用次数: 7

Wavelet-based estimation of long-memory noise in Diffuse Optical Imaging 漫射光学成像中基于小波的长记忆噪声估计

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541017

C. Matteau-Pelletier, M. Dehaes, F. Lesage, J. Lina

引用次数: 0

Quantified brain asymmetry for age estimation of normal and AD/MCI subjects 量化脑不对称对正常和AD/MCI受试者年龄的估计

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541295

Leonid Teverovskiy, J. Becker, O. Lopez, Yanxi Liu

{"title":"Quantified brain asymmetry for age estimation of normal and AD/MCI subjects","authors":"Leonid Teverovskiy, J. Becker, O. Lopez, Yanxi Liu","doi":"10.1109/ISBI.2008.4541295","DOIUrl":"https://doi.org/10.1109/ISBI.2008.4541295","url":null,"abstract":"We propose a quantified asymmetry based method for age estimation. Our method uses machine learning to discover automatically the most discriminative asymmetry feature set from different brain regions and image scales. Applying this regression model on a Tl MR brain image set of 246 healthy individuals (121 females; 125 males, 66 plusmn 7.5 years old), we achieve a mean absolute error of 5.4 years and a mean signed error of -0.2 years for age estimation on unseen MR images using the stringent leave-15%-out cross validation. Our results show significant changes in asymmetry with aging in the following regions: the posterior horns of the lateral ventricles, the amygdala, the ventral putamen with a nearby region of the anterior inferior caudate nucleus, the basal fore- brain, hyppocampus and parahyppocampal regions. We confirm the validity of the age estimation model using permutation test on 30 replicas of the original dataset with randomly permuted ages (with p-value < 0.001). Furthermore, we apply this model to a separate set of MR images containing normal, Alzheimer's disease (AD) and mild cognitive impairment (MCI) subjects. Our results reflect the relative severity of brain pathology between the three subject groups: mean signed age estimation error is 0.6 years for normal controls, 2.2 years for MCI patients, and 4.7 years for AD patients.","PeriodicalId":184204,"journal":{"name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121493434","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: 10

Locally adaptive fuzzy pulmonary vessel segmentation in contrast enhanced CT data 增强CT数据局部自适应模糊肺血管分割

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4540942

J. Kaftan, A. Bakai, M. Das, T. Aach

引用次数: 16