Chen H C, Chen C K, Yang T H, Kuo L C, Jou I M, Su F C, Sun Y N
Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, ROC.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:8009-12. doi: 10.1109/IEMBS.2011.6091975.
Trigger finger is a common hand disease, causing swelling, painful popping and clicking in moving the affected finger joint. To better evaluate patients with trigger finger, segmentation of flexor tendons from magnetic resonance (MR) images of finger joints, which can offer detailed structural information of tendons to clinicians, is essential. This paper presents a novel model-based method with three stages for automatically segmenting the flexor tendons. In the first stage, a set of tendon contour models (TCMs) is initialized from the most proximal cross-sectional image via two-step ellipse estimation. Each of the TCMs is then propagated to its distally adjacent image by affine registration. The propagation is sequentially performed along the proximal-distal direction until the most distal image is reached, as the second stage of segmentation. The TCMs on each cross-sectional image are refined in the last stage with the snake deformation. MR volumes of three subjects were used to validate the segmentation accuracy. Compared with the manual results, our method showed good accuracy with small average margins of errors (within 0.5 mm) and large overlapping ratio (dice similarity coefficient above 0.8). Overall, the proposed method has great potential for morphological change assessment of flexor tendons and pulley-tendon system modeling for image guided surgery.
扳机指是一种常见的手部疾病，会导致受影响的手指关节肿胀、活动时出现疼痛的弹响和卡嗒声。为了更好地评估扳机指患者，从手指关节的磁共振（MR）图像中分割屈肌腱至关重要，因为这可以为临床医生提供肌腱的详细结构信息。本文提出了一种基于模型的新颖方法，分三个阶段自动分割屈肌腱。在第一阶段，通过两步椭圆估计从最近端的横截面图像初始化一组肌腱轮廓模型（TCM）。然后，通过仿射配准将每个TCM传播到其相邻的远端图像。分割的第二阶段是沿着近端-远端方向顺序进行传播，直到到达最远端的图像。在最后阶段，使用蛇形变形对每个横截面图像上的TCM进行细化。使用三名受试者的MR容积来验证分割精度。与手动结果相比，我们的方法显示出良好的准确性，平均误差 margin 较小（在0.5毫米以内）且重叠率较高（骰子相似系数高于0.8）。总体而言，所提出的方法在屈肌腱形态变化评估和图像引导手术的滑车-肌腱系统建模方面具有巨大潜力。
