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A Variable Background Active Contour Model for Automatic Detection of Thyroid Nodules in Ultrasound Images

机译:用于自动检测超声图像中甲状腺结节的可变背景主动轮廓模型

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A novel active contour model named Variable Background Active Contour model is proposed and applied for the detection of thyroid nodules in ultrasound images. The new model offers edge independency, no need for smoothing, ability for topological changes and it is more accurate when compared to the Active Contour Without Edges model. Improved accuracy is achieved by introducing as background a limited image subset which appropriately changes shape to reduce the effects of background inhomogeneity. We validated the proposed model on ultrasound images acquired from 24 patients and the results demonstrate an improvement in accuracy when compared to the Active Contour Without Edges model.
机译:提出了一种名为VARIACT CONTOUT模型的新型活性轮廓模型,并施加用于检测超声图像中的甲状腺结节。新型号提供边缘独立性,无需平滑,拓扑变化的能力,与没有边缘模型的活动轮廓相比,它更准确。通过作为背景引入有限的图像子集来实现提高的精度,该图像子集适当地改变形状以减少背景不均匀性的影响。我们验证了从24名患者获取的超声图像上提出的模型,结果与没有边缘模型的有源轮廓相比,结果表现出准确性的提高。

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