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Prostate contours delineation using interactive directional active contours model and parametric shape prior model

机译:使用交互式定向主动轮廓模型和参数形状先验模型进行前列腺轮廓勾画

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Prostate contours delineation on Magnetic Resonance (MR) images is a challenging and important task in medical imaging with applications of guiding biopsy,surgery and therapy.While a fully automated method is highly desired for this application,it can be a very difficult task due to the structure and surrounding tissues of the prostate gland.Traditional active contours-based delineation algorithms are typically quite successful for piecewise constant images.Nevertheless,when MR images have diffuse edges or multiple similar objects (e.g. bladder close to prostate) within close proximity,such approaches have proven to be unsuccessful.In order to mitigate these problems,we proposed a new framework for bi-stage contours delineation algorithm based on directional active contours(DAC)incorporating prior knowledge of the prostate shape.We first explicitly addressed the prostate contour delineation problem based on fast globally DAC that incorporates both statistical and parametric shape prior model.In doing so,we were able to exploit the global aspects of contour delineation problem by incorporating a user feedback in contours delineation process where it is shown that only a small amount of user input can sometimes resolve ambiguous scenarios raised by DAC.In addition,once the prostate contours have been delineated,a cost functional is designed to incorporate both user feedback interaction and the parametric shape prior model.Using data from publicly available prostate MR datasets,which includes several challenging clinical datasets,we highlighted the effectiveness and the capability of the proposed algorithm.Besides,the algorithm has been compared with several state-of-the-art methods. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:在引导活检,手术和治疗的医学成像中,在磁共振(MR)图像上描绘前列腺轮廓是一项具有挑战性和重要的任务。尽管此方法非常需要全自动方法,但由于以下原因,这可能是一项非常困难的任务:传统的基于主动轮廓的描绘算法通常对于分段恒定图像非常成功。尽管如此,当MR图像在靠近时具有弥散的边缘或多个相似的物体(例如,靠近前列腺的膀胱)时,例如为了缓解这些问题,我们提出了一种基于方向活动轮廓(DAC)并结合了前列腺​​形状的先验知识的双阶段轮廓描绘算法的新框架。我们首先明确地解决了前列腺轮廓描绘问题基于快速全局DAC的问题,该DAC兼具统计和参数形状先验通过这样做,我们能够通过在轮廓描绘过程中合并用户反馈来利用轮廓描绘问题的全局方面,其中表明只有少量用户输入才能解决DAC提出的模棱两可的情况。 ,一旦确定了前列腺轮廓,就设计了一种成本功能,以结合用户反馈交互和参数形状先验模型。使用来自公开可用的前列腺MR数据集的数据,其中包括一些具有挑战性的临床数据集,我们强调了有效性和能力此外,该算法已与几种最新方法进行了比较。版权所有(c)2015 John Wiley&Sons,Ltd.

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