北京生物醫(yī)學(xué)工程

基于SHOT與目標(biāo)函數(shù)對(duì)稱ICP的低重疊率術(shù)前術(shù)中點(diǎn)云配準(zhǔn)算法

Low overlap rate preoperative and intraoperative point cloud registration algorithm based on SHOT and symmetric objective function ICP

作者：嚴(yán)文磬張立靜王瑋武博

單位：首都醫(yī)科大學(xué)生物醫(yī)學(xué)工程學(xué)院（北京 100069）<br />首都醫(yī)科大學(xué)臨床生物力學(xué)應(yīng)用基礎(chǔ)研究北京市重點(diǎn)實(shí)驗(yàn)室（北京 100069)<br />首都醫(yī)科大學(xué)宣武醫(yī)院（北京 100053)<br />通信作者：武博，副教授。E-mail：[email protected]

關(guān)鍵詞：點(diǎn)云配準(zhǔn)；SHOT；目標(biāo)函數(shù)對(duì)稱ICP；低重疊率

分類號(hào)：R318.04

出版年·卷·期（頁(yè)碼）：2023·42·2（111-116）

摘要：

目的配準(zhǔn)是術(shù)前影像引導(dǎo)的椎弓根螺釘內(nèi)固定術(shù)中的重要環(huán)節(jié)。術(shù)前CT影像三維重建獲得的點(diǎn)云和術(shù)中捕獲的暴露部位點(diǎn)云重疊率低，易受噪聲、遮擋等因素的干擾，使點(diǎn)云配準(zhǔn)更具挑戰(zhàn)性。本文采用局部特征和距離度量相結(jié)合的方式應(yīng)對(duì)低重疊率配準(zhǔn)問(wèn)題。方法首先利用方向直方圖描述子(signature of histograms of orientations, SHOT)描述子和隨機(jī)抽樣一致算法(random sample consensus, RANSAC)提取并匹配幾何特征相似的點(diǎn)，完成初始對(duì)齊。應(yīng)用目標(biāo)函數(shù)對(duì)稱ICP，通過(guò)最小化對(duì)稱化點(diǎn)到面目標(biāo)函數(shù)得到最終變換矩陣。對(duì)來(lái)源于SpineWeb公開數(shù)據(jù)集的5組腰椎數(shù)據(jù)進(jìn)行配準(zhǔn)實(shí)驗(yàn)。結(jié)果術(shù)前術(shù)中點(diǎn)云配準(zhǔn)實(shí)驗(yàn)中平均配準(zhǔn)誤差為0.128 mm，平均運(yùn)行時(shí)間為5.750 s。結(jié)論實(shí)驗(yàn)結(jié)果驗(yàn)證了該算法在低重疊率術(shù)前術(shù)中點(diǎn)云配準(zhǔn)中的有效性，使得醫(yī)生能及時(shí)根據(jù)配準(zhǔn)結(jié)果調(diào)整手術(shù)器械，從而提高椎弓根螺釘置入準(zhǔn)確率。

Objective Registration is an important part of preoperative image-guided pedicle screw fixation. The point cloud obtained by the 3D reconstruction of the preoperative CT image and the point cloud of the exposed part captured during the operation have a low overlap rate and are easily interfered by factors such as noise and occlusion, which makes the point cloud registration more challenging. This paper adopted the combination of local geometric features and distance measurement to deal with the problem of low overlap registration. Methods Firstly, the points with similar geometric features were extracted and matched using the signature of histograms of orientations descriptor(SHOT) and the random sample consensus(RANSAC) to complete the initial alignment. Applying the objective function symmetric ICP algorithm, the final transformation matrix was obtained by minimizing the symmetric point-to-surface objective function. Registration experiments were performed on five groups of lumbar spine data from the SpineWeb public dataset. Results In the preoperative and intraoperative point cloud registration experiments, the average registration error was 0.128 mm, and the average running time was 5.750 s. Conclusions The experimental results verify the effectiveness of the algorithm in the preoperative and intraoperative point cloud registration with low overlap rate, which enables doctors to adjust the surgical instruments according to the registration results in time, thus improving the accuracy of pedicle screw placement.

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