Evaluating image denoising methods in myocardial perfusion single photon emission computed tomography (SPECT) imaging
Evaluating image denoising methods in myocardial perfusion single photon emission computed tomography (SPECT) imaging
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DOI：
10.1088/0957-0233/20/10/104023
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发表时间：
2009-10-01
影响因子：
2.4
通讯作者：
Panayiotakis, G.
中科院分区：
文献类型：
--
作者：
Skiadopoulos, S.;Karatrantou, A.;Panayiotakis, G.
由于泊松噪声效应，单光子发射计算机断层扫描（SPECT）成像的统计性质导致图像质量下降，特别是在低信噪比（SNR）病变的情况下。各种成熟的单尺度去噪方法应用于投影原始图像已被纳入SPECT成像应用，而多尺度去噪方法已被提出有前途的性能。在本文中，多尺度血小板去噪方法和成熟的巴特沃思滤波器作为前处理和后处理步骤的图像重建没有和/或衰减校正之间进行比较评估研究。采用（i）包含两种不同尺寸冷缺陷的心脏体模进行定量评价，用于模拟无和有心肌周围组织光子衰减条件的两项实验，以及（ii）15例缺血性缺陷患者的试点验证临床数据集。计算体模和患者缺陷的图像噪声、缺陷对比度、SNR和缺陷对比噪声比（CNR）指标。此外，根据两名核医学临床医生的排名，对临床数据集进行了观察者偏好研究。在没有光子衰减条件的情况下，对于大尺寸缺陷，通过血小板和巴特沃思后处理方法的去噪优于巴特沃思预处理，而对于小尺寸缺陷以及光子衰减条件，所有方法都表现出相似的去噪性能。在两种衰减条件下，血小板方法在未进行衰减校正的情况下重建的图像在缺陷对比度、SNR和缺陷CNR方面表现出改善的性能，但不具有统计学显著性（p > 0.05）。从临床数据中获得的定量和偏好结果表明，所研究的去噪方法具有相似的性能。总之，与应用于投影或重建图像的巴特沃思滤波器相比，应用于原始投影图像的多尺度血小板降噪方法提供了更有效的降噪，同时保持了心肌体模SPECT成像中的图像质量。然而，在没有或有衰减校正的情况下重建的临床数据上没有观察到这种有利于血小板去噪方法的趋势。
The statistical nature of single photon emission computed tomography (SPECT) imaging, due to the Poisson noise effect, results in the degradation of image quality, especially in the case of lesions of low signal-to-noise ratio (SNR). A variety of well-established single-scale denoising methods applied on projection raw images have been incorporated in SPECT imaging applications, while multi-scale denoising methods with promising performance have been proposed. In this paper, a comparative evaluation study is performed between a multi-scale platelet denoising method and the well-established Butterworth filter applied as a pre- and post-processing step on images reconstructed without and/or with attenuation correction. Quantitative evaluation was carried out employing (i) a cardiac phantom containing two different size cold defects, utilized in two experiments conducted to simulate conditions without and with photon attenuation from myocardial surrounding tissue and (ii) a pilot-verified clinical dataset of 15 patients with ischemic defects. Image noise, defect contrast, SNR and defect contrast-to-noise ratio (CNR) metrics were computed for both phantom and patient defects. In addition, an observer preference study was carried out for the clinical dataset, based on rankings from two nuclear medicine clinicians. Without photon attenuation conditions, denoising by platelet and Butterworth post-processing methods outperformed Butterworth pre-processing for large size defects, while for small size defects, as well as with photon attenuation conditions, all methods have demonstrated similar denoising performance. Under both attenuation conditions, the platelet method showed improved performance with respect to defect contrast, SNR and defect CNR in the case of images reconstructed without attenuation correction, however not statistically significant (p > 0.05). Quantitative as well as preference results obtained from clinical data showed similar performance of the denoising methods studied. In conclusion, the multi-scale platelet denoising method applied on raw projection images provides more efficient noise reduction while preserving image quality in a myocardial phantom SPECT imaging as compared to the Butterworth filter applied either on projection or reconstructed images. However, this trend in favour of the platelet denoising method was not observed on clinical data reconstructed either without or with attenuation correction.