多尺度边缘检测与参数化边界形状建模 光声图像的描绘

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摘要翻译：
在这篇文章中，我们提出了一种新的图像边界分割方案（与背景）在光声小动物在体成像系统。该方法利用多尺度边缘检测算法生成二值边缘图。利用尺度相关的形态学运算来清除杂散边缘。然后，通过约束参数变换和迭代拟合优度计算将椭圆拟合到边缘映射中。该方法通过曲线拟合模型来确定组织边缘，具有较高的精度。因此，该方法消除了多尺度处理中的尺度选择和等高线映射中种子点的确定，从而使光声光图像的分割具有最小的人为干预。
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英文标题：
《Multiscale edge detection and parametric shape modeling for boundary
  delineation in optoacoustic images》
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作者：
Subhamoy Mandal, Viswanath Pamulakanty Sudarshan, Yeshaswini Nagaraj,
  Xose Luis Dean Ben, Daniel Razansky
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最新提交年份：
2015
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分类信息：

一级分类：Physics        物理学
二级分类：Medical Physics        医学物理学
分类描述：Radiation therapy. Radiation dosimetry. Biomedical imaging modelling.  Reconstruction, processing, and analysis. Biomedical system modelling and analysis. Health physics. New imaging or therapy modalities.
放射治疗。辐射剂量学。生物医学成像建模。重建、处理和分析。生物医学系统建模与分析。健康物理学。新的成像或治疗方式。
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一级分类：Computer Science        计算机科学
二级分类：Computer Vision and Pattern Recognition        计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Image and Video Processing        图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
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英文摘要：
  In this article, we present a novel scheme for segmenting the image boundary (with the background) in optoacoustic small animal in vivo imaging systems. The method utilizes a multiscale edge detection algorithm to generate a binary edge map. A scale dependent morphological operation is employed to clean spurious edges. Thereafter, an ellipse is fitted to the edge map through constrained parametric transformations and iterative goodness of fit calculations. The method delimits the tissue edges through the curve fitting model, which has shown high levels of accuracy. Thus, this method enables segmentation of optoacoutic images with minimal human intervention, by eliminating need of scale selection for multiscale processing and seed point determination for contour mapping.
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PDF链接：
https://arxiv.org/pdf/1506.03124

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关键词：Construction Segmentation Presentation Calculations intervention 方法 boundary optoacoustic 具有 detection