Segmentation of diffuse reflectance hyperspectral datasets with noise for detection of Melanoma.
Segmentation of diffuse reflectance hyperspectral datasets with noise for detection of Melanoma.
复制标题
用于检测黑色素瘤的带有噪声的漫反射高光谱数据集的分割。
DOI：
10.1109/embc.2012.6346221
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Markey,MiaK
中科院分区：
文献类型：
--
作者：
Hennessy,Ricky;Bish,Sheldon;Tunnell,JamesW;Markey,MiaK
我们提出了一种分割算法，允许光学特性从漫反射高光谱数据集提取的三个数量级的速度比目前的方法。这些数据可用于检测黑色素瘤。该算法首先使用主成分分析进行降维，然后使用k均值聚类进行图像分割。然后计算每个聚类的平均光谱，并可用于提取化学信息。通过减少要分析的光谱的数量，生理信息的提取可以比需要分析高光谱数据集中的每个光谱的方法快三个数量级。使用数字体模测试了噪声对算法准确分割图像能力的影响，其中噪声水平由研究人员控制。分析表明，噪声水平与该算法能够准确检测和分割的最小散射差异之间存在线性关系。这一发现可用于确定成像系统中仍允许检测非黑素瘤和黑素瘤之间光学性质差异的最大噪声量。
We present a segmentation algorithm that allows optical properties to be extracted from diffuse reflectance hyperspectral datasets with a speedup of three orders of magnitude when compared to current methods. Such data could be used for the detection of melanoma. The algorithm first performs dimensionality reduction using principal component analysis, and then the image is segmented using k-means clustering. The mean spectrum from each cluster is then calculated and can be used to extract chemical information. By reducing the number of spectra to be analyzed, extraction of physiological information can be achieved three orders of magnitude faster than methods requiring the analysis of every spectrum in the hyperspectral dataset. The effect of noise on the ability of the algorithm to accurately segment images was tested using digital phantoms, for which the noise level was under the control of the investigators. The analysis showed a linear relationship between the level of noise and the smallest difference in scattering that the algorithm was able to accurately detect and segment. This finding can be used to determine the maximum amount of noise in the imaging system that will still allow detection of the difference in optical properties between non-melanoma and melanoma.