Development and evaluation of spectral classification algorithms for fluorescence guided laser angioplasty.
Development and evaluation of spectral classification algorithms for fluorescence guided laser angioplasty.
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荧光引导激光血管成形术光谱分类算法的开发和评估。
DOI：
10.1109/10.18748
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发表时间：
1989
期刊：
影响因子：
--
通讯作者：
Deckelbaum,LI
中科院分区：
文献类型：
--
作者：
O'Brien,KM;Gmitro,AF;Gindi,GR;Stetz,ML;Cutruzzola,FW;Laifer,LI;Deckelbaum,LI
考虑利用光谱信息来区分动脉组织类型的可行性。从 100 份人类主动脉标本中获得了 350 至 700 nm 的动脉荧光光谱。使用以下技术开发了七种光谱分类算法：多元线性回归、逐步多元线性回归、主成分分析、决策平面分析、贝叶斯决策理论、主峰比和光谱宽度。每个算法的分类能力通过将其应用于训练集和包含 82 个附加光谱的验证集来评估。所有七种光谱分类算法都对动脉粥样硬化和正常主动脉进行了前瞻性分类，准确率超过 80%（范围：82-96%）。因此，结合光谱分类算法的激光血管成形系统可能能够检测和选择性消融动脉粥样硬化斑块。<>
The feasibility of utilizing spectral information to discriminate arterial tissue type is considered. Arterial fluorescence spectra from 350 to 700 nm were obtained from 100 human aortic specimens. Seven spectral classification algorithms were developed with the following techniques: multivariate linear regression, stepwise multivariate linear regression, principal components analysis, decision plane analysis, Bayes decision theory, principal peak ratio, and spectral width. The classification ability of each algorithm was evaluated by its application to the training set and to a validation set containing 82 additional spectra. All seven spectral classification algorithms prospectively classified atherosclerotic and normal aortas with an accuracy greater than 80% (range: 82-96%). Laser angioplasty systems incorporating spectral classification algorithms may therefore be capable of detection and selective ablation of atherosclerotic plaque.<>