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Fuzzy Segmentation of the Left Ventricle in Cardiac MRI Using Physiological Constraints

机译:使用生理制约因素在心脏MRI中的左心室的模糊分割

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We describe a general framework for adapting existing segmentation algorithms, such that the need for optimisation of intrinsic, potentially unintuitive parameters is minimized, focusing instead on applying intuitive physiological constraints. This allows clinicians to easily influence existing tools of their choice towards outcomes with physiological properties that are more relevant to their particular clinical contexts, without having to deal with the optimisation specifics of a particular algorithm's intrinsic parameters. This is achieved by a structured exploration of the parameter space resulting in a subspace of relevant segmentations, and by subsequent fusion biased towards segmentations that best adhere to the imposed constraints. We demonstrate this technique on an algorithm used by a validated, and freely available cardiac segmentation suite (Segment - http://segment.heiberg.se).
机译:我们描述了一种适应现有分割算法的一般框架,使得对固有的优化,潜在的不完全参数的需要最小化,而是对施加直观的生理限制来说。这使得临床医生能够轻松地影响他们选择的现有工具,以与他们的特定临床环境更相关的生理特性,而不必处理特定算法的内在参数的优化细节。这是通过对参数空间的结构化探索来实现的,导致相关分割子空间,随后融合偏向最佳粘附于强加的约束的分段。我们在验证和自由的心脏分割套件(段 - http://segent.hebiberg.se)上使用的算法上演示了这种技术。

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