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首页> 外文期刊>Journal of digital imaging: the official journal of the Society for Computer Applications in Radiology >Semi-automated phalanx bone segmentation using the expectation maximization algorithm.
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Semi-automated phalanx bone segmentation using the expectation maximization algorithm.

机译:使用期望最大化算法半自动的Phalanx骨分割。

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摘要

Medical imaging technologies have allowed for in vivo exploration and evaluation of the human musculoskeletal system. Three-dimensional bone models generated using image-segmentation techniques provide a means to optimize individualized orthopedic surgical procedures using engineering analyses. However, many of the current segmentation techniques are not clinically practical due to the required time and human intervention. As a proof of concept, we demonstrate the use of an expectation maximization (EM) algorithm to segment the hand phalanx bones, and hypothesize that this semi-automated technique will improve the efficiency while providing similar definitions as compared to a manual rater. Our results show a relative overlap of the proximal, middle, and distal phalanx bones of 0.83, 0.79, and 0.72 for the EM technique when compared to validated manual segmentations. The EM segmentations were also compared to 3D surface scans of the cadaveric specimens, which resulted in distance maps showing an average distance for the proximal, middle, and distal phalanx bones of 0.45, 0.46, and 0.51 mm, respectively. The EM segmentation improved on the segmentation speed of the manual techniques by a factor of eight. Overall, the manual segmentations had greater relative overlap metric values, which suggests that the manual segmentations are a better fit to the actual surface of the bone. As shown by the comparison to the bone surface scans, the EM technique provides a similar representation of the anatomic structure and offers an increase in efficiency that could help to reduce the time needed for defining anatomical structures from CT scans.
机译:医学成像技术允许体内探索和评估人肌肉骨骼系统。使用图像分割技术产生的三维骨模型提供了使用工程分析优化个体化整形外科手术的方法。然而,由于所需的时间和人为干预,许多当前的分段技术在临床上不实际。作为概念证明,我们展示了使用预期最大化(EM)算法来分割手机骨骼,并假设该半自动化技术将提高效率,同时与手动评估者提供类似的定义。与验证的手动分割相比,我们的结果显示了0.83,0.79和0.72的近端,中间和远端骨骼为0.83,0.79和0.72的相对重叠。同样将EM分段与尸体标本的3D表面扫描进行比较,导致距离图分别显示近端,中间和远端骨骼的平均距离,分别为0.45,0.46和0.51mm。 EM分段改善了手动技术的分割速度占八倍。总的来说,手动分段具有更大的相对重叠度量值,这表明手动分段是更好的骨骼的拟合。如通过与骨表面扫描的比较所示,EM技术提供了解剖结构的类似表示,并提高了有助于减少来自CT扫描的解剖结构所需的时间。

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