Pandey Anil Kumar, Kaur Gagandeep, Chaudhary Jagrati, Hemrom Angel, Jaleel Jasim, Sharma Param Dev, Patel Chetan, Kumar Rakesh
Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India.
Department of Computer Science, SGTB Khalsa College, University of Delhi, New Delhi, India.
Indian J Nucl Med. 2023 Jan-Mar;38(1):8-15. doi: 10.4103/ijnm.ijnm_78_22. Epub 2023 Feb 24.
In this pilot study, we have proposed and evaluated pipelined application of the dynamic stochastic resonance (DSR) algorithm and block-matching 3D (BM3D) filter for the enhancement of nuclear medicine images. The enhanced images out of the pipeline were compared with the corresponding enhanced images obtained using individual applications of and algorithm.
Twenty 99m-Tc MDP bone scan images acquired on SymbiaT6 SPECT/CT gamma camera system fitted with low-energy high-resolution collimators were exported in format to a personal computer and converted into format. These images were processed using the proposed algorithm in . Two nuclear medicine physicians visually compared each input and its corresponding three enhanced images to select the best-enhanced image. The image quality metrics (, , (CPP), and ) were used to assess the image quality objectively. The Wilcoxon signed test was applied to find a statistically significant difference in , of enhanced and its input images at a level of significance.
Images enhanced using the pipelined application of SR and BM3D were selected as the best images by both nuclear medicine physicians. Based on , (GCF), CPP, and , the image quality of our proposed pipeline was significantly better than enhanced images obtained using individual applications of and algorithm. The proposed method was found to be very successful in enhancing details in the low count region of input images. The enhanced images were bright, smooth, and had better target-to-background ratio compared to input images.
The pipelined application of and algorithm produced enhancement in nuclear medicine images having following characteristics: bright, smooth, better target-to-background ratio, and improved visibility of details in the low count regions of the input image, as compared to individual enhancements by application of or algorithm.
在本初步研究中，我们提出并评估了动态随机共振（DSR）算法和三维块匹配（BM3D）滤波器的流水线应用，以增强核医学图像。将流水线输出的增强图像与使用DSR算法和BM3D算法单独应用获得的相应增强图像进行比较。
在配备低能高分辨率准直器的SymbiaT6 SPECT/CT伽马相机系统上采集的20幅99m-Tc MDP骨扫描图像以DICOM格式导出到个人计算机并转换为NIfTI格式。这些NIfTI图像在MATLAB中使用所提出的算法进行处理。两名核医学医师对每个输入图像及其相应的三幅增强图像进行视觉比较，以选择最佳增强图像。使用图像质量指标（对比度、均匀性、对比噪声比（CNR）和清晰度）客观地评估图像质量。应用Wilcoxon符号检验以在显著性水平α = 0.05下发现增强图像与其输入图像在对比度、均匀性方面的统计学显著差异。
使用SR和BM3D的流水线应用增强的图像被两位核医学医师都选为最佳图像。基于对比度、均匀性（GCF）、CNR和清晰度，我们提出的流水线的图像质量明显优于使用DSR算法和BM3D算法单独应用获得的增强图像。发现所提出的方法在增强输入图像低计数区域的细节方面非常成功。与输入图像相比，增强图像明亮、平滑，且具有更好的目标与背景比。
与单独应用DSR算法或BM3D算法进行增强相比，DSR算法和BM3D算法的流水线应用在核医学图像中产生了具有以下特征的增强效果：明亮、平滑、更好的目标与背景比，以及输入图像低计数区域细节可见性的改善。
