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首页> 外文会议>Conference on Biomedical Applications in Molecular, Structural, and Functional Imaging >Algorithmic evaluation of lower jawbone segmentations
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Algorithmic evaluation of lower jawbone segmentations

机译：较低颚骨分段的算法评估

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The lower jawbone (or mandible), is due to its exposure to complex biomechanical forces the largest and strongest facial bone in humans. In this publication, an algorithmic evaluation of lower jawbone segmentation with a cellular automata algorithm called GrowCut is presented. For an evaluation, the algorithmic segmentation results were compared with slice-by-slice segmentations from two specialized physicians, which is considered to assess the given ground truth. As a result, pure manual slice-by-slice outlining took on average 39 minutes (minimum 35 minutes and maximum 46 minutes). This stands in strong contrast to an algorithmic segmentation which needed only about one minute for an initialization, hence needing just a fraction of the manual contouring time. At the same time, the algorithmic segmentations could achieve an acceptable Dice Similarity Score (DSC) of nearly ninety percent when compared to the ground truth slice-by-slice segmentations generated by the physicians. This stands in direct comparison to somewhat above ninety percent Dice Score between the two manual segmentations of the jawbones. In summary, this contribution shows that an algorithmic GrowCut segmentation can be an alternative to the very time consuming manual slice-by-slice outlining in the clinical practice.
机译：下颌颚酮（或下颌骨）是由于其暴露于复杂的生物力学力量是人类中最大和最强的面部骨骼。在本出版物中，提出了一种具有蜂窝自动机算法的较低抖动分割的算法评估。为了评估，将算法分割结果与来自两个专业医师的逐片分段进行比较，这被认为是评估给定的基础事实。因此，纯手动切片概述平均39分钟（最小35分钟，最大46分钟）。这与算法分割相比，算法分割具有强烈对比，该算法分割对于初始化仅需要大约一分钟，因此需要仅需要手动轮廓件的一小部分。同时，与医生产生的地面真理切片分割相比，算法分割可以实现近90％的可接受的骰子相似度分数（DSC）。这与Jawbone的两种手动分段之间的略高于百分之九十百分之九十的骰子分数直接比较。总之，该贡献表明，算法生长分段可以是临床实践中非常耗时的手动切片逐切片的替代方案。

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