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Generic and robust method for automatic segmentation of PET images using an active contour model

机译:使用活动轮廓模型自动分割PET图像的通用和鲁棒方法

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Purpose: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies.
机译:目的:尽管正电子发射断层扫描(PET)图像显示出潜力,以提高靶向靶向靶向疗效的准确性,但由于低空间分辨率和固有的肿瘤肿瘤的界限不容易区分。 宠物图像的嘈杂特征。 本研究的目的是利用活性轮廓模型来开发一种用于自动描绘肿瘤体积的通用和鲁棒方法,并使用幻影和临床研究评估其性能。

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