Department of Radiological Technology, School of Health Sciences, Niigata University, Asahimachi-dori, Chuo-ku, Niigata, Niigata, Japan.
Department of Medical Radiological Technology, School of Health Sciences, Fukushima Medical University, Sakae-machi, Fukushima, Fukushima, Japan.
J Xray Sci Technol. 2022;30(4):777-788. doi: 10.3233/XST-221142.
Head computed tomography (CT) is a commonly used imaging modality in radiology facilities. Since multiplanar reconstruction (MPR) processing can produce different results depending on the medical staff in charge, there is a possibility that the antemortem and postmortem images of the same person could be assessed and identified differently.
To propose and test a new automatic MPR method in order to address and overcome this limitation.
Head CT images of 108 cases are used. We employ the standardized transformation of statistical parametric mapping 8. The affine transformation parameters are obtained by standardizing the captured CT images. Automatic MPR processing is performed by using this parameter. The sphenoidal sinus of the orbitomeatal cross section of the automatic MPR processing of this study and the conventional manual MPR processing are cropped with a matrix size of 128×128, and the value of zero mean normalized correlation coefficient is calculated.
The computed zero mean normalized cross-correlation coefficient (Rzncc) of≥0.9, 0.8≤Rzncc < 0.9 and 0.7≤Rzncc < 0.8 are achieved in 105 cases (97.2%), 2 cases (1.9%), and 1 case (0.9%), respectively. The average Rzncc was 0.96±0.03.
Using the proposed new method in this study, MPR processing with guaranteed accuracy is efficiently achieved.
头部计算机断层扫描（CT）是放射科常用的成像方式。由于多平面重建（MPR）处理的结果可能因负责的医务人员而异，因此同一人的生前和死后图像有可能被不同地评估和识别。
提出并测试一种新的自动 MPR 方法，以解决和克服这一限制。
使用 108 例头部 CT 图像。我们采用标准化的统计参数映射 8 转换。通过对捕获的 CT 图像进行标准化，获得仿射变换参数。使用该参数进行自动 MPR 处理。通过自动 MPR 处理和常规手动 MPR 处理截取研究中的蝶窦眶耳断面的眼眶，矩阵大小为 128×128，并计算零均值归一化相关系数的值。
在 105 例（97.2%）、2 例（1.9%）和 1 例（0.9%）中分别达到计算的零均值归一化交叉相关系数（Rzncc）≥0.9、0.8≤Rzncc<0.9 和 0.7≤Rzncc<0.8。平均 Rzncc 为 0.96±0.03。
使用本研究提出的新方法，可以有效地实现具有保证准确性的 MPR 处理。
