Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1007/978-3-030-00931-1_53 |
Exploratory Population Analysis with Unbalanced Optimal Transport | |
Gerber, Samuel1; Niethammer, Marc2; Styner, Martin2; Aylward, Stephen1 | |
通讯作者 | Gerber, Samuel |
会议名称 | 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) |
会议日期 | SEP 16-20, 2018 |
会议地点 | Granada, SPAIN |
英文摘要 | The plethora of data from neuroimaging studies provide a rich opportunity to discover effects and generate hypotheses through exploratory data analysis. Brain pathologies often manifest in changes in shape along with deterioration and alteration of brain matter, i.e., changes in mass. We propose a morphometry approach using unbalanced optimal transport that detects and localizes changes in mass and separates them from changes due to the location of mass. The approach generates images of mass allocation and mass transport cost for each subject in the population. Voxelwise correlations with clinical variables highlight regions of mass allocation or mass transfer related to the variables. We demonstrate the method on the white and gray matter segmentations from the OASIS brain MRI data set. The separation of white and gray matter ensures that optimal transport does not transfer mass between different tissues types and separates gray and white matter related changes. The OASIS data set includes subjects ranging from healthy to mild and moderate dementia, and the results corroborate known pathology changes related to dementia that are not discovered with traditional voxel-based morphometry. The transport-based morphometry increases the explanatory power of regression on clinical variables compared to traditional voxel-based morphometry, indicating that transport cost and mass allocation images capture a larger portion of pathology induced changes. |
来源出版物 | MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, PT III |
ISSN | 0302-9743 |
EISSN | 1611-3349 |
出版年 | 2018 |
卷号 | 11072 |
页码 | 464-472 |
ISBN | 978-3-030-00930-4 |
EISBN | 978-3-030-00931-1 |
出版者 | SPRINGER INTERNATIONAL PUBLISHING AG |
类型 | Proceedings Paper |
语种 | 英语 |
国家 | USA |
收录类别 | CPCI-S |
WOS记录号 | WOS:000477769700053 |
WOS关键词 | VOXEL-BASED MORPHOMETRY |
WOS类目 | Computer Science, Theory & Methods ; Imaging Science & Photographic Technology |
WOS研究方向 | Computer Science ; Imaging Science & Photographic Technology |
资源类型 | 会议论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/307269 |
作者单位 | 1.Kitware Inc, Carborro, NC 27510 USA; 2.Univ N Carolina, Chapel Hill, NC 27504 USA |
推荐引用方式 GB/T 7714 | Gerber, Samuel,Niethammer, Marc,Styner, Martin,et al. Exploratory Population Analysis with Unbalanced Optimal Transport[C]:SPRINGER INTERNATIONAL PUBLISHING AG,2018:464-472. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。