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首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.8,no.31; Proceedings of SPIE-The International Society for Optical Engineering; vol.6512 pt.3 >Fully Automatic Estimation of Object Pose for Segmentation Initialization: Application to Cardiac MR and Echocardiography Images
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Fully Automatic Estimation of Object Pose for Segmentation Initialization: Application to Cardiac MR and Echocardiography Images

机译：用于分段初始化的目标姿势的全自动估计：在心脏MR和超声心动图图像中的应用

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摘要

Automatic image segmentation techniques are essential for medical image interpretation and analysis. Though numerous methods on image segmentation have been reported, the quality of a segmentation often heavily relies on the positioning of an accurate initial contour. In this paper, a novel solution is presented for the automated object detection in medical image data. A shape- and intensity template is generated from a training set, and both the search image and the template are mapped into a log-polar domain, where rotation and scale are represented by a translation. Orientation and scale of the object are estimated by determining maximum normalized correlation using a Symmetric Phase Only Matched Filter (SPOMF) with a peak enhancement filter. The detected orientation and scale are subsequently applied to the template, and a second pass of the SPOMF using the transformed template yields the actual position of the object in the search image. Performance tests were carried out on two imaging modalities: a set of cardiac MRI images from 34 patients and 2D echocardiograms from 100 patients.
机译：自动图像分割技术对于医学图像解释和分析至关重要。尽管已经报道了许多关于图像分割的方法，但是分割的质量通常在很大程度上取决于精确的初始轮廓的定位。在本文中，提出了一种用于医学图像数据中自动对象检测的新颖解决方案。从训练集中生成形状和强度模板，然后将搜索图像和模板都映射到对数极域中，其中旋转和比例由平移表示。通过使用带有峰值增强滤波器的仅对称相位匹配滤波器（SPOMF）确定最大归一化相关性，可以估算对象的方向和比例。随后将检测到的方向和比例应用于模板，使用转换后的模板对SPOMF进行第二次遍历，将得出对象在搜索图像中的实际位置。对两种成像方式进行了性能测试：来自34位患者的一组心脏MRI图像和来自100位患者的2D超声心动图。

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