【摘要】：針對傳統(tǒng)面繪制方法隨真實(shí)感的提升效率急劇下降,且交互性及靈敏度較差的問題,基于CT點(diǎn)云數(shù)據(jù)提出了一種肝臟病灶的表面重建方法。首先改進(jìn)了點(diǎn)云數(shù)據(jù)的插值和自適應(yīng)精簡方法;然后提出將模型重構(gòu)過程分為兩部分,先通過最小能量約束和簡化的MC算法由點(diǎn)云距離場快速創(chuàng)建粗糙的基底模型,接著提出一種線性最優(yōu)化的ARDP算法用于自動計算點(diǎn)元投影向量,從而將當(dāng)前模型表面節(jié)點(diǎn)直接映射至點(diǎn)云,通過交互式地確定迭代次數(shù)可按需逐步提高模型精確度,最終獲取高質(zhì)量模型,實(shí)現(xiàn)散亂點(diǎn)到平滑面的直接過渡。實(shí)驗結(jié)果表明,利用該算法生成平均誤差小于0.000 1的高精模型將大大縮短時間,且對不規(guī)則病灶模型有著良好的適應(yīng)性。
[Abstract]:In order to solve the problem that the efficiency of traditional surface rendering method decreases sharply with the improvement of reality, and the interaction and sensitivity are poor, a surface reconstruction method for liver lesions is proposed based on CT point cloud data. Firstly, the interpolation and adaptive reduction of point cloud data are improved, and then the reconstruction process of the model is divided into two parts. Firstly, the rough base model is created by the minimum energy constraint and the simplified MC algorithm from the point cloud distance field. Then a linear optimization ARDP algorithm is proposed to calculate the projection vector of point element automatically, so that the surface nodes of the current model can be mapped directly to the point cloud, and the accuracy of the model can be improved step by interactively determining the number of iterations. Finally, a high quality model is obtained to realize the direct transition from scattered points to smooth surfaces. The experimental results show that the algorithm can greatly shorten the time and has a good adaptability to the irregular focus model by generating a high-precision model with an average error of less than 0.000 1.
【作者單位】： 福州大學(xué)物理與信息工程學(xué)院;
【基金】：國家自然科學(xué)基金(No.61471124) 福建省自然科學(xué)基金(No.2013J05090) 福建省科技計劃重點(diǎn)項目(No.2011H0027)
【分類號】：R575;R816.5;TP391.41
，

本文編號：2228336