Application of Numerical Observer CHO in Evaluation of Filtering Method in PET
Xie Jing1, Yang Yong1*, Ye Hongwei2*, Chen Dongmei1
1School of Biomedical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China 2Min Found Medical System Corporation Ltd., Shaoxing 312000, Zhejiang, China
Abstract：In clinical applications, it is necessary to limit the scan time and dose, which tends to lower the resolution of the positron emission tomography (PET) image and increase the noisein PET. A denoise method is required to achieve the clinically acceptable images, and a post filter after reconstruction is the most widely used method. Therefore, the comparison of smoothing effect of different filters, for instance the selection of filter parameters, is an important step in PET image reconstruction. Generally, the signal-to-noise ratio (SNR), recovery coefficient (RC) or similar methods are used in the parameter selections. But researchers still rely on their experience since those methods cannot be used quantitatively. As a generalized numerical observer, channelized hotelling observer (CHO) has been used in selection of various parameters in PET, such as reconstruction algorithm parameters, system design parameters, clinical protocol parameters and so on. However its application in the assessment of different filtering methods of image reconstruction is not widely studied. The purpose of this paper is to select the optimal parameters of two widely used filters, i.e. Gauss filter and Non-Local Mean (NLM) filter, and evaluate their smoothing effect in PET by comparing the area under the receiver operating characteristic(ROC)curve (AUC) values calculated by CHO. Experimental results showed that for the 13 mm sphere, Gauss filter with σ of1.1~1.4 and NLM filter with f of 0.5-0.9 achieved the maximum detectability, and for the 10 mm sphere, Gauss filter with σ of 1.4~2.0 and NLM filter with f of 0.5~0.9 achieved the maximum detectability. Though AUC values of both filters were as high as 0.9, the AUC value of NLM filter was larger than that of Gauss filter. It was also found out that bright spots had better contrast and lower noise in IEC images and patient images with the NLM filter than that with the Gauss filter. This conclusion was consistent with results obtained by traditional evaluation methods of the filter, which indicated that CHO accurately compared the performance of these two filters in the lesion detection task of PET.
谢靓, 杨勇, 叶宏伟, 陈冬梅. CHO数字观察器在PET图像滤波方法评估中的应用[J]. 中国生物医学工程学报, 2017, 36(6): 661-669.
Xie Jing, Yang Yong, Ye Hongwei, Chen Dongmei. Application of Numerical Observer CHO in Evaluation of Filtering Method in PET. Chinese Journal of Biomedical Engineering, 2017, 36(6): 661-669.
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