KST-Mixer: kinematic spatio-temporal data mixer for colon shape estimation
KST-Mixer: kinematic spatio-temporal data mixer for colon shape estimation
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KST-Mixer：用于结肠形状估计的运动时空数据混合器
DOI：
10.1080/21681163.2022.2151938
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Kensaku Mori
中科院分区：
文献类型：
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作者：
Masahiro Oda;Kazuhiro Furukawa;Nassir Navab;Kensaku Mori
我们提出了一种时空混合的运动学数据估计方法来估计结肠镜插入所造成的变形的结肠的形状。需要内窥镜跟踪或导航系统将医生导航到目标位置，以减少器官穿孔等并发症。尽管许多先前的方法集中于跟踪支气管镜和外科内窥镜，但是很少提出结肠镜跟踪方法，因为结肠在结肠镜插入期间很大程度上变形。这种变形会导致很大的跟踪误差。在跟踪过程中应考虑结肠变形。我们提出了一种使用运动时空数据混合器（KST-Mixer）的结肠形状估计方法，该方法可在结肠镜插入结肠期间使用。使用电磁和深度传感器获得结肠镜和结肠的运动学数据，包括它们的中心线的位置和方向。所提出的方法将数据分成子组沿沿着的空间和时间轴。KST混合器提取运动学特征并沿轴沿着多次混合它们。我们评估了结肠形状估计的准确性，在幻影研究。该方法实现了11.92 mm的平均欧氏距离误差，是以前方法中最小的。统计分析表明，所提出的方法显着减少了错误相比，以前的方法。
We propose a spatio-temporal mixing kinematic data estimation method to estimate the shape of the colon with deformations caused by colonoscope insertion. Endoscope tracking or a navigation system that navigates physicians to target positions is needed to reduce such complications as organ perforations. Although many previous methods focused to track bronchoscopes and surgical endoscopes, few number of colonoscope tracking methods were proposed because the colon largely deforms during colonoscope insertion. The deformation causes significant tracking errors. Colon deformation should be considered in the tracking process. We propose a colon shape estimation method using a Kinematic Spatio-Temporal data Mixer (KST-Mixer) that can be used during colonoscope insertions to the colon. Kinematic data of a colonoscope and the colon, including positions and directions of their centerlines, are obtained using electromagnetic and depth sensors. The proposed method separates the data into sub-groups along the spatial and temporal axes. The KST-Mixer extracts kinematic features and mix them along the axes multiple times. We evaluated colon shape estimation accuracies in phantom studies. The proposed method achieved 11.92 mm mean Euclidean distance error, the smallest of the previous methods. Statistical analysis indicated that the proposed method significantly reduced the error compared to the previous methods.