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101.
Segmentation of the left ventricle (LV) is a hot topic in cardiac magnetic resonance (MR) images analysis. In this paper, we present an automatic LV myocardial boundary segmentation method using the parametric active contour model (or snake model). By convolving the gradient map of an image, a fast external force named gradient vector convolution (GVC) is presented for the snake model. A circle-based energy is incorporated into the GVC snake model to extract the endocardium. With this prior constraint, the snake contour can conquer the unexpected local minimum stemming from artifacts and papillary muscle, etc. After the endocardium is detected, the original edge map around and within the endocardium is directly set to zero. This modified edge map is used to generate a new GVC force filed, which automatically pushes the snake contour directly to the epicardium by employing the endocardium result as initialization. Meanwhile, a novel shape-similarity based energy is proposed to prevent the snake contour from being strapped in faulty edges and to preserve weak boundaries. Both qualitative and quantitative evaluations on our dataset and the publicly available database (e.g. MICCAI 2009) demonstrate the good performance of our algorithm. 相似文献
102.
Pingkun Yan Wuxia Zhang Baris Turkbey Peter L. Choyke Xuelong Li 《Computer Vision and Image Understanding》2013,117(9):1017-1026
Organ shape plays an important role in clinical diagnosis, surgical planning and treatment evaluation. Shape modeling is a critical factor affecting the performance of deformable model based segmentation methods for organ shape extraction. In most existing works, shape modeling is completed in the original shape space, with the presence of outliers. In addition, the specificity of the patient was not taken into account. This paper proposes a novel target-oriented shape prior model to deal with these two problems in a unified framework. The proposed method measures the intrinsic similarity between the target shape and the training shapes on an embedded manifold by manifold learning techniques. With this approach, shapes in the training set can be selected according to their intrinsic similarity to the target image. With more accurate shape guidance, an optimized search is performed by a deformable model to minimize an energy functional for image segmentation, which is efficiently achieved by using dynamic programming. Our method has been validated on 2D prostate localization and 3D prostate segmentation in MRI scans. Compared to other existing methods, our proposed method exhibits better performance in both studies. 相似文献
103.
Jungchan Cho Minsik Lee Chong-Ho Choi Songhwai Oh 《Computer Vision and Image Understanding》2013,117(11):1549-1559
Aligning shapes is essential in many computer vision problems and generalized Procrustes analysis (GPA) is one of the most popular algorithms to align shapes. However, if some of the shape data are missing, GPA cannot be applied. In this paper, we propose EM-GPA, which extends GPA to handle shapes with hidden (missing) variables by using the expectation-maximization (EM) algorithm. For example, 2D shapes can be considered as 3D shapes with missing depth information due to the projection of 3D shapes into the image plane. For a set of 2D shapes, EM-GPA finds scales, rotations and 3D shapes along with their mean and covariance matrix for 3D shape modeling. A distinctive characteristic of EM-GPA is that it does not enforce any rank constraint often appeared in other work and instead uses GPA constraints to resolve the ambiguity in finding scales, rotations, and 3D shapes. The experimental results show that EM-GPA can recover depth information accurately even when the noise level is high and there are a large number of missing variables. By using the images from the FRGC database, we show that EM-GPA can successfully align 2D shapes by taking the missing information into consideration. We also demonstrate that the 3D mean shape and its covariance matrix are accurately estimated. As an application of EM-GPA, we construct a 2D + 3D AAM (active appearance model) using the 3D shapes obtained by EM-GPA, and it gives a similar success rate in model fitting compared to the method using real 3D shapes. EM-GPA is not limited to the case of missing depth information, but it can be easily extended to more general cases. 相似文献
104.
文中对传统围油栏进行形状优化,应用流体体积分数法(VOF),数值模拟优化后的围油栏对两种不同粘度油类拦油效果;通过分析、比较拦油失效速度、失效时间以及围油栏失效前的栏前受压,说明围油栏形状优化的可行性,以提高围油栏的拦油性能。 相似文献
105.
国内某大型水电工程的混凝土骨料母岩为洞挖大理岩渣料,应用中面临岩性较脆、料源均一性欠佳、毛料含水率大、粗骨料裹粉严重且级配较差、干法生产的人工砂石粉含量超标严重等诸多问题。大理岩人工骨料大规模用于大型水电工程,并采用干式制砂系统,在国内尚属首次。根据工程建设中长期的跟踪检测数据,针对上述问题进行了深入剖析,提出了增加缓降装置和二次筛分及水洗装置、采用胶带运输、调整主筛分车间筛网、筛除毛料中大于20 mm的颗粒、调整风选车间参数等相应对策。在取得较好的技术效果的同时,为类似工程的进一步大范围应用积累了经验。 相似文献
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109.
目前,自动语音识别系统往往会因为环境中复杂因素的影响,造成训练环境和测试环境存在不匹配现象,使得识别系统性能大幅度下降,极大地限制了语音识别技术的应用范围。近年来,很多鲁棒语音识别技术成功地被提出,这些技术的目标都是相同的,主要是提高系统的鲁棒性,进而提高识别率。其中,基于特征的归一化技术简单而有效,常常被作为鲁棒语音识别的首选方法,它主要是通过对特征向量的统计属性、累积密度函数或功率谱的归一化来补偿环境不匹配产生的影响。该文主要对目前主流的归一化方法进行介绍,其中包括倒谱矩归一化方法、直方图均衡化方法以及调频谱归一化方法等。 相似文献
110.
软件内嵌探针测试是在探针函数模板的框架内编写被测对象,并对被测对象进行面向对象软件的常规测试,在观察预期结果与实际结果是否一致的同时,还要察看探针函数输出的信息,以确定对象的状态是否正确。本论文研究的重点在于探针函数的构成、探针函数的实现及内嵌探针测试方法的应用研究,意在构筑一个基本的应用框架,提供一种实用的测试方法。 相似文献