2D ultrasound image segmentation using graph cuts and local image features

机译：使用图形切割和局部图像特征进行2D超声图像分割

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摘要

Ultrasound imaging is a popular imaging modality due to a number of favorable properties of this modality. However, the poor quality of ultrasound images makes them a bad choice for segmentation algorithms. In this paper, we present a semi-automatic algorithm for organ segmentation in ultrasound images, by posing it as an energy minimization problem via appropriate definition of energy terms. We use graph-cuts as our optimization algorithm and employ a fuzzy inference system (FIS) to further refine the optimization process. This refinement is achieved by using the FIS to incorporate domain knowledge in order to provide additional constraints. We show that by integrating domain knowledge via FIS, the accuracy is improved significantly so that further manual refinement of object boundary is often unnecessary. Our algorithm was applied to detect prostate and carotid artery boundaries in clinical ultrasound images and shows the success of the proposed approach.

机译：由于该模态具有许多有利的特性，因此超声成像是一种流行的成像模态。但是，超声图像质量差使它们成为分割算法的错误选择。在本文中，我们通过适当定义能量项将其视为能量最小化问题，提出了一种超声图像中器官分割的半自动算法。我们使用图割作为优化算法，并采用模糊推理系统（FIS）进一步优化优化过程。通过使用FIS合并领域知识以提供附加约束，可以实现这种改进。我们表明，通过FIS集成领域知识，可以显着提高准确性，因此通常不需要进一步手动优化对象边界。我们的算法被应用于在临床超声图像中检测前列腺和颈动脉边界，并证明了该方法的成功。

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《Computational Intelligence for Image Processing, 2009. CIIP '09》|2009年|33-40|共8页
会议地点 Nashville TN(US);Nashville TN(US)
作者
Zouqi M.; Samarabandu J.;
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Dept. of Electr. Comput. Eng., Univ. of Western Ontario, London, ON;

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biomedical ultrasonics; fuzzy set theory; graph theory; image segmentation; inference mechanisms; medical image processing; optimisation; 2D ultrasound image segmentation; carotid artery boundary detection; fuzzy inference system; graph cuts; image features; optimization algorithm; prostate boundary detection; ultrasound imaging;

机译：生物医学超声;模糊集理论;图论;图像分割;推理机制;医学图像处理;优化;二维超声图像分割;颈动脉边界检测;模糊推理系统;图割;图像特征;优化算法;前列腺边界检测;超声影像学;

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1. A Dynamic Graph Cuts Method with Integrated Multiple Feature Maps for Segmenting Kidneys in 2D Ultrasound Images [J] . Qiang Zheng, Steven Warner, Gregory Tasian, Academic radiology . 2018,第9期

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2. Segmentation of 3-D High-Frequency Ultrasound Images of Human Lymph Nodes Using Graph Cut With Energy Functional Adapted to Local Intensity Distribution [J] . Jen-wei Kuo, Jonathan Mamou, Yao Wang, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control . 2017,第10期

机译：使用适应局部强度分布的能量函数图割对人淋巴结的3D高频超声图像进行分割
3. Improved graph cut model with features of superpixels and neighborhood patches for myocardium segmentation from ultrasound image [J] . Song Xiangfen, Wang Yinong, Feng Qianjin, Annals of the American Thoracic Society . 2019,第3期

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4. 2D Ultrasound Image Segmentation Using Graph Cuts and Local Image Features [C] . Mehrnaz Zouqi, Jagath Samarabandu IEEE Symposium on Computational Intelligence for Image Processing . 2009

机译：使用曲线图和本地图像特征2d超声图像分割
5. Computer-aided segmentation of anatomical features in transrectal ultrasound prostate images. [D] . Pathak, Sayan Dev. 2000

机译：经直肠超声前列腺图像中解剖特征的计算机辅助分割。
6. A dynamic graph-cuts method with integrated multiple feature maps for segmenting kidneys in 2D ultrasound images [O] . Qiang Zheng, Steven Warner, Gregory Tasian, -1

机译：具有集成多特征图的动态图割方法用于在二维超声图像中分割肾脏
7. Segmentation of 3D High-frequency Ultrasound Images of Human Lymph Nodes Using Graph Cut with Energy Functional Adapted to Local Intensity Distribution [O] . Kuo, Jen-wei, Mamou, Jonathan, Wang, Yao, 2017

机译：人体淋巴结三维高频超声图像的分割使用具有能量函数的图形切割适应局部强度分配

2D ultrasound image segmentation using graph cuts and local image features

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