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Paraspinal muscle segmentation in CT images using a single atlas

机译:使用单个地图集的CT图像中的肩胛骨分割

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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:肩胛骨肌肉支持脊柱,是运动势力。横截面区域(CSA)尺寸,形状,密度和体积受许多因素的影响,例如手术,年龄,健康状况,运动和低腰痛。引入微创脊柱外科(未命中)以提供较少的肌肉组织损伤,术后疼痛和早期动员,而不是传统的开放式手术。 CT图像中的肩胛骨CSA和体积的手动测量不准确和耗时。在这项工作中,基于地图集的图像配准用于在CT图像中划分肌肉区域。为了解决肌肉形状和区域方向的大变化的挑战,在全局登记后进行局部轮廓优化。实验结果表明,该方法可以成功地在目标图像中成功分段椎间围肌肉区域。结果可用于评估椎间弹性肌肉体积,因此组织损伤和术后患者术后患者萎缩。

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