2013 IEEE 10th International Symposium on Biomedical Imaging最新文献_第9页

MEG source reconstruction constrained by diffusion MRI based whole brain dynamical model 基于扩散核磁共振全脑动力学模型约束的脑磁图源重构

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556646

M. Fukushima, O. Yamashita, T. Knösche, Masa-aki Sato

引用次数: 4

Efficient GRAPPA reconstruction using random projection 基于随机投影的高效GRAPPA重建

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556571

Jingyuan Lyu, Yuchou Chang, L. Ying

引用次数: 3

Weakly supervised semantic segmentation of Crohn's disease tissues from abdominal MRI 腹部MRI对克罗恩病组织的弱监督语义分割

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556607

D. Mahapatra, A. Vezhnevets, P. Schüffler, J. Tielbeek, F. Vos, J. Buhmann

引用次数: 28

Automatic normal-abnormal video frame classification for colonoscopy 用于结肠镜检查的正常-异常视频帧自动分类

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556557

Siyamalan Manivannan, Ruixuan Wang, E. Trucco, A. Hood

引用次数: 31

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556455

Yongning Lu, Ying Sun, Rui Liao, S. Ong

{"title":"A new similarity measure for deformable image registration based on intensity matching","authors":"Yongning Lu, Ying Sun, Rui Liao, S. Ong","doi":"10.1109/ISBI.2013.6556455","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556455","url":null,"abstract":"Deformable image registration plays an important role in medical image analysis. Multi-modal image registration remains a challenging research topic due to the complexity of modeling the relationship between two images. Mutual information (MI) is widely used in the field of multi-modal image registration, however, it suffers from problems such as interpolation artifacts and/or statistical insufficiency. The problem is worsened when bias field and noise are present. There have been attempts to map images to a common modality before image registration process, but the error introduced by the mapping may be detrimental to the registration. In this paper, instead of explicitly mapping the images to a common modality, we introduce a new similarity measure based on intensity matching information, which can be learnt from the existing registered training pairs or images pairs registered by performing MI based registration. Experiments on simulated brain MRI and real myocardial perfusion MR image sequences indicate that our proposed similarity measure outperforms the conventional MI and Kroon and Slump's method [1].","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115454810","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: 1

Sparse component selection with application to MEG source localization 稀疏分量选择及其在MEG源定位中的应用

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556535

Martin Luessi, M. Hämäläinen, V. Solo

引用次数: 3

Semi-automatic catheter model generation using biplane x-ray images 利用双翼x线图像半自动生成导管模型

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556799

S. Kaeppler, Wen Wu, Terrence Chen, M. Koch, A. Kiraly, Norbert Strobel, J. Hornegger

引用次数: 1

A non-parametric method based on NBNN for automatic detection of liver lesion in CT images 基于NBNN的CT图像肝脏病变自动检测的非参数方法

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556488

Wei Yang, Qianjin Feng, Meiyan Huang, Zhentai Lu, Wufan Chen

引用次数: 5

Drift correction for fluorescence live cell imaging through correlated motion identification 通过相关运动识别的荧光活细胞成像漂移校正

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556509

Minhua Qiu, Ge Yang

{"title":"Drift correction for fluorescence live cell imaging through correlated motion identification","authors":"Minhua Qiu, Ge Yang","doi":"10.1109/ISBI.2013.6556509","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556509","url":null,"abstract":"Fluorescence live cell imaging is an important experimental technique for visualizing and recording dynamic cellular processes under physiological conditions. However, a problem commonly encountered during imaging is sample drift. Without correction, such drift will cause bias or even error in subsequent image analysis of intracellular movement. Traditional area-based and feature-based image registration techniques often fail to correct such drift because, in addition to whole cell drift, intracellular features of interest also undergo separate and complex motion. To address this problem, we developed an image registration technique based on identifying clusters of features that undergo highly correlated motion. Sample drift is determined from movement of these features and corrected. Experiments confirmed that this technique can effectively remove translational drift with sub-pixel accuracy. For drift that also involves rotation, an extension of the technique is developed to determine rotation angles both within and out of the image plane so that rotational drift can be corrected. The technique is general and can be used for drift correction in a broad range of biological studies.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125250368","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

Group sparse dictionary learning and inference for resting-state fMRI analysis of Alzheimer'S disease 分组稀疏字典学习与推理用于阿尔茨海默病静息态fMRI分析

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556531

Jeonghyeon Lee, Y. Jeong, J. C. Ye

{"title":"Group sparse dictionary learning and inference for resting-state fMRI analysis of Alzheimer'S disease","authors":"Jeonghyeon Lee, Y. Jeong, J. C. Ye","doi":"10.1109/ISBI.2013.6556531","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556531","url":null,"abstract":"A novel group analysis tool for data-driven resting state fMRI analysis using group sparse dictionary learning and mixed model is presented along with the promising indications of Alzheimer's disease progression. Instead of using independency assumption as in popular ICA approaches, the proposed approach is based on the sparse graph assumption such that a temporal dynamics at each voxel position is a sparse combination of global brain dynamics. In estimating the unknown global dynamics and local network structures, we perform sparse dictionary learning for the concatenated temporal data across the subjects by constraining that the network structures within a group are similar. Under the homoscedasticity variance assumption across subjects and groups, we show that the mixed model group inference can be easily performed using second level GLM with summary statistics. Using extensive resting fMRI data set obtained from normal, Mild Cognitive Impairment (MCI), Clinical Dementia Rating scale (CDR) 0.5, CDR 1.0, and CDR 2.0 of Alzheimer's disease patients groups, we demonstrated that the changes of default mode network extracted by the proposed method is more closely correlated with the progression of Alzheimer's disease.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122392854","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: 14