基于级联adaboost的CT心脏图像自动分割中的初始定位研究
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摘要
从CT影像中自动提取心脏结构信息是心脏影像大数据处理的一个必然趋势,也是减轻医生工作量的迫切需求,但其中的一个重要步骤是心脏的自动初始定位。为此,论文将Haar-like和adaboost级联分类器相结合,用于心脏的初始定位。论文完成了该方法的实现,准备了大量的正样本和副样本,完成了训练过程的参数调试,并对实际CT心脏图像进行了测试。结果表明论文采用的方法是可行的,为下一步全自动提取心脏结构做好了良好的准备。
引文
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[3] Marsden A, Esmaily-Moghadam M. Multiscale Modeling of Cardiovascular Flows for Clinical Decision Support[J]. Applied Mechanics Reviews, 2015,67:030804.
[4] Kayvanpour E, Mansi T, Sedaghat-Hamedani F, et al. Towards personalized cardiology:Multi-scale modeling of the failing heart[J]. PLoS ONE, 2015,10(7):1–18.
[5] Zhu L, Gao Y, Appia V, et al. A complete system for automatic extraction of left ventricular myocardium from CT images using shape segmentation and contour evolution[J]. IEEE Transactions on Image Processing, 2014,23(3):1340–51.
[6] Ha T, Kim K, Lim S, et al. Three-dimensional Reconstruction of a Cardiac Outline by Magnetocardiography[J]. IEEE Transactions on Biomedical Engineering,2014, 9294(c):1–10.
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[9] Ecabert O, Peters J, Schramm H, et al. Automatic model-based segmentation of the heart in CT images[J]. IEEE Transactions on Medical Imaging, 2008, 27(9):1189–201.
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[11] Zhu L, Gao Y, Yezzi A, et al. Automatic segmentation of the left atrium from MR images via variational region growing with a momentsbased shape prior[J]. IEEE Transactions on Image Processing, 2013,22(12):5111–22.
[12] Zhen X, Wang Z, Islam A, et al. Multi-scale deep networks and regression forests for direct bi-ventricular volume estimation[J]. Medical Image Analysis, 2016, 30:120–129.
[13] Mansoor A, Cerrolaza J J, Idrees R, et al. Deep Learning Guided Partitioned Shape Model for Anterior Visual Pathway Segmentation[J]. IEEE Transactions on Medical Imaging, 2016, 35(8):1856–1865.
[14] Lienhart R, Maydt J. An extended set of Haar-like features for rapid object detection[C]//International Conference on Image Processing.2002, 1:I-900-I-903.
[15] Viola P, Jones MJ. Robust Real-Time Face Detection[J].International Journal of Computer Vision, 2004,57(2):137–154.