Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision最新文献

Cortex segmentation - a fast variational geometric approach 皮层分割-一种快速变分几何方法

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938891

Roman Goldenberg, R. Kimmel, E. Rivlin, M. Rudzsky

引用次数: 29

Fiber tract mapping from diffusion tensor MRI 磁共振弥散张量成像纤维束

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938885

Baba C. Vemuri, Yun Chen, M. Rao, Tim McGraw, Zhizhou Wang, T. Mareci

引用次数: 105

Stability of image restoration by minimizing regularized objective functions 最小化正则化目标函数的图像恢复稳定性

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938884

S. Durand, M. Nikolova

{"title":"Stability of image restoration by minimizing regularized objective functions","authors":"S. Durand, M. Nikolova","doi":"10.1109/VLSM.2001.938884","DOIUrl":"https://doi.org/10.1109/VLSM.2001.938884","url":null,"abstract":"We address the general problem of the recovery of an unknown image, x/spl isin/R/sup p/, from noisy data, y/spl isin/R/sup q/, by minimizing a regularized objective function /spl epsi/(x,y). We focus on typical situations when the objective function is C/sup m/-smooth and is composed of a quadratic data-fidelity term and a general regularization term: /spl epsi/(x,y)=/spl par/Ax-y/spl par//sup 2/+/spl Phi/(x), where A is a linear operator. Many authors have shown that especially nonconvex regularizers /spl Phi/ allow the restoration of images involving both sharp edges and smoothly varying regions. The main limitation in using such regularizers is that, being highly nonconvex, the resultant objective functions are intricate to minimize. On the other hand since very few facts are known about the minimizers of such functions, the properties and in particular the stability of the resultant solutions are difficult to control. This state of the art limits the practical use of such functions. This work is devoted to the stability of the local and global minimizers x of objective functions /spl epsi/ as specified above, under the assumption that A is injective. We thus have shown that the global minimizers of /spl epsi/ are stable under small perturbations of the data.","PeriodicalId":445975,"journal":{"name":"Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122226741","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: 5

3D automated segmentation and structural analysis of vascular trees using deformable models 三维自动分割和维管树结构分析使用可变形模型

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938890

Derek R. Magee, A. Bulpitt, E. Berry

{"title":"3D automated segmentation and structural analysis of vascular trees using deformable models","authors":"Derek R. Magee, A. Bulpitt, E. Berry","doi":"10.1109/VLSM.2001.938890","DOIUrl":"https://doi.org/10.1109/VLSM.2001.938890","url":null,"abstract":"This paper describes novel automated methods for the segmentation of complex structures and their subsequent analysis. The methods have been developed as parts of a system to provide decision support in the assessment of patient suitability for endovascular repair of abdominal aortic aneurysms from spiral CT data. Our segmentation technique provides a new method for controlling the deformation: a 3D deformable model using a model of expected structure. This approach introduces knowledge of anatomy into the deformable model through an expected structure model (ESM), mimicking the knowledge of the observer in an interactive system. The expected structure model is used to improve robustness of the deformable model to noise within the image, without globally over-constraining the model. The model also permits the identification of features of interest that can be used for clinical assessment. In order to obtain useful measurements from the segmentations, the geometric structure of the arterial tree is required. Our method automates this procedure using a stochastic growing algorithm based on a particle filter to determine the centre lines and locations of bifurcations of the arterial tree. The results demonstrate how the ESM and stochastic growing algorithm can be used to both identify features and to produce measurements required for patient assessment.","PeriodicalId":445975,"journal":{"name":"Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116229545","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: 15

Flame front matching and tracking in PLIF images using geodesic paths and level sets 使用测地线路径和水平集的PLIF图像中的火焰前匹配和跟踪

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938889

R. Abu-Gharbieh, C. Kaminski, T. Gustavsson, G. Hamarneh

引用次数: 10

Affine invariant edge completion with affine geodesics 仿射测地线的仿射不变边补全

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938887

A. A. Handzel, T. Flash

引用次数: 4

Optimal mass transport and image registration 最佳质量传输和图像配准

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938878

S. Haker, A. Tannenbaum

引用次数: 18

A variational approach to multi-modal image matching 多模态图像匹配的变分方法

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938877

C. Chefd'Hotel, G. Hermosillo, O. Faugeras

引用次数: 125

On affine invariance in the Beltrami framework for vision 视觉Beltrami框架中的仿射不变性

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938881

N. Sochen

引用次数: 8

On smoothness measures of active contours and surfaces 关于活动轮廓和表面的平滑度量

Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision Pub Date : 2001-07-13 DOI: 10.1109/VLSM.2001.938880

Hervé Delingette

引用次数: 11