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Paraspinal muscle segmentation in CT images using a single atlas

机译:使用单个图集在CT图像中进行椎旁肌肉分割

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Paraspinal muscles support spine and are the source of movement force. The cross section area (CSA) size, shape, density and volume are affected by many factors, such as surgery, age, health condition, exercise, and low back pain. Minimally invasive spine surgery (MISS) was introduced to provide less muscle tissue injury, less postoperative pain and earlier mobilization than traditional open back surgery. Manual measurements of paraspinal muscle CSA and volume in CT images is inaccurate and time consuming. In this work, an atlas-based image registration is used to segment the muscle region in CT images. In order to address the challenge of large variations of muscle shape and region direction, a local contour optimization is performed after global registration. Experimental results show that the proposed method can successfully segment paraspinal muscle regions in target images. The results can be used to evaluate paraspinal muscle volume hence tissue injury and postoperative back muscle atrophy of MISS patients.
机译:脊柱旁肌肉支撑脊柱,是运动力的来源。横截面积(CSA)的大小,形状,密度和体积受许多因素影响,例如手术,年龄,健康状况,运动和下背部疼痛。引入微创脊柱外科手术(MISS)可以提供比传统的开放式背部手术更少的肌肉组织损伤,更少的术后疼痛和更早的动员。在CT图像中手动测量椎旁肌CSA和体积是不准确且耗时的。在这项工作中,基于图集的图像配准用于分割CT图像中的肌肉区域。为了解决肌肉形状和区域方向变化很大的挑战,在全局配准后执行局部轮廓优化。实验结果表明,该方法可以成功分割目标图像中的椎旁肌区域。该结果可用于评估MISS患者的椎旁肌肉体积,组织损伤和术后背部肌肉萎缩。

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