Adaptive spectral window sizes for extraction of diagnostic features from optical spectra.

Adaptive spectral window sizes for extraction of diagnostic features from optical spectra.
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用于从光谱中提取诊断特征的自适应光谱窗口大小。

DOI:
10.1117/1.3481143
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发表时间:
2010
影响因子:
3.5
通讯作者:
Markey,MiaK
Markey,MiaK
中科院分区:
医学3区
文献类型:
--
作者:
Kan,Chih-wen;Lee,AndyY;Nieman,LindaT;Sokolov,Konstantin;Markey,MiaK

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我们提出了一种自适应调整光谱窗口大小以进行光谱特征提取的方法。以前的研究从固定宽度的光谱窗口中提取特征。在我们的算法中,分段线性回归被用来自适应地调整窗口大小,以找到与光谱具有合理线性拟合的最大窗口大小。这种自适应加窗技术确保了信号在定义窗口中的线性度;因此,自适应加窗技术在使用较少窗口的同时保留了更多诊断信息。该方法进行了测试的数据集上的漫反射光谱的口腔粘膜病变。从每个窗口提取八个特征。我们使用线性判别分析与交叉验证进行分类。使用窗口技术的结果在更好的分类性能比不使用窗口。对于正常与轻度异型增生(MD)加重度高度异型增生或癌(SD)以及良性与非异型增生(MD),窗口技术的受试者工作特征曲线下面积均大于非窗口技术。虽然自适应和固定大小的窗口执行类似,自适应窗口使用的窗口明显少于固定大小的窗口(每个频谱的窗口数:8对16)。由于自适应窗口保留了大多数诊断信息,同时减少了特征提取所需的窗口数量,我们的研究结果表明,它隔离了光谱中独特的诊断特征。
We present an approach to adaptively adjust the spectral window sizes for optical spectra feature extraction. Previous studies extracted features from spectral windows of a fixed width. In our algorithm, piecewise linear regression is used to adaptively adjust the window sizes to find the maximum window size with reasonable linear fit with the spectrum. This adaptive windowing technique ensures the signal linearity in defined windows; hence, the adaptive windowing technique retains more diagnostic information while using fewer windows. This method was tested on a data set of diffuse reflectance spectra of oral mucosa lesions. Eight features were extracted from each window. We performed classifications using linear discriminant analysis with cross-validation. Using windowing techniques results in better classification performance than not using windowing. The area under the receiver-operating-characteristics curve for windowing techniques was greater than a nonwindowing technique for both normal versus mild dysplasia (MD) plus severe high-grade dysplasia or carcinama (SD)and benign versus. Although adaptive and fixed-size windowing perform similarly, adaptive windowing utilizes significantly fewer windows than fixed-size windows (number of windows per spectrum: 8 versus 16). Because adaptive windows retain most diagnostic information while reducing the number of windows needed for feature extraction, our results suggest that it isolates unique diagnostic features in optical spectra.
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