Linguraru Marius George, Vasilyev Nikolay V, Del Nido Pedro J, Howe Robert D
Division of Engineering and Applied Sciences, Harvard Medical School, Harvard University, Cambridge, and Department of Cardiac Surgery, Children's Hospital, Boston, MA, USA.
Ultrasound Med Biol. 2007 Sep;33(9):1428-37. doi: 10.1016/j.ultrasmedbio.2007.03.003. Epub 2007 May 22.
The recent development of real-time 3-D ultrasound (US) enables intracardiac beating-heart procedures, but the distorted appearance of surgical instruments is a major challenge to surgeons. In addition, tissue and instruments have similar gray levels in US images and the interface between instruments and tissue is poorly defined. We present an algorithm that automatically estimates instrument location in intracardiac procedures. Expert-segmented images are used to initialize the statistical distributions of blood, tissue and instruments. Voxels are labeled through an iterative expectation-maximization algorithm using information from the neighboring voxels through a smoothing kernel. Once the three classes of voxels are separated, additional neighboring information is combined with the known shape characteristics of instruments to correct for misclassifications. We analyze the major axis of segmented data through their principal components and refine the results by a watershed transform, which corrects the results at the contact between instrument and tissue. We present results on 3-D in-vitro data from a tank trial and 3-D in-vivo data from cardiac interventions on porcine beating hearts, using instruments of four types of materials. The comparison of algorithm results to expert-annotated images shows the correct segmentation and position of the instrument shaft.
实时三维超声（US）技术的最新发展使得心脏内跳动心脏手术成为可能，但手术器械的变形外观对外科医生来说是一个重大挑战。此外，在超声图像中组织和器械具有相似的灰度，并且器械与组织之间的界面定义不清晰。我们提出了一种在心脏内手术中自动估计器械位置的算法。使用专家分割的图像来初始化血液、组织和器械的统计分布。通过迭代期望最大化算法，利用平滑核从相邻体素获取的信息对体素进行标记。一旦将三类体素分离，将额外的相邻信息与器械已知的形状特征相结合，以纠正错误分类。我们通过主成分分析分割数据的主轴，并通过分水岭变换细化结果，该变换在器械与组织的接触处校正结果。我们展示了来自水箱试验的三维体外数据以及来自对猪跳动心脏进行心脏干预的三维体内数据的结果，使用了四种材料类型的器械。算法结果与专家标注图像的比较显示了器械轴的正确分割和定位。
