Performance Evaluation of Implicit Neural Representations in Diagnostic Fan-Beam CT Imaging

doi:doi.org/10.1007/978-3-031-75653-5_4

	Performance Evaluation of Implicit Neural Representations in Diagnostic Fan-Beam CT Imaging
	2024-10-11
	Wenhui, Qin1 ; Zhentao, Liu 1; Xiaopeng, Yu 1; Mengqing, Su 2; Yang, Yang 2; Yikun, Zhang 2; Yuyao, Zhang 3; Zhiming, Cui 1; Yang, Chen 2; Xiaochun, Lai1
来源专著	Deep Learning for Advanced X-ray Detection and Imaging Applications
出版地	Gewerbestrasse 11, 6330 Cham, Switzerland
出版者	Springer, Cham
摘要	Recently, implicit neural representation (INR) has been widely applied in computed tomography (CT) reconstruction, achieving impressive results in sparse view reconstruction and metal artifacts reduction with high peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values. In this chapter, we conduct a comprehensive evaluation of INR’s effectiveness in fan-beam CT applications using the metrics accredited by the American College of Radiology (ACR), such as CT number accuracy, low-contrast detectability, and spatial resolution. Our studies show that, despite demonstrating potential, further refinement of INR-based techniques is needed to fully harness their capabilities in clinical applications, in terms of CT number accuracy, low-contrast detectability, spatial resolution, and free of artifacts.
DOI	doi.org/10.1007/978-3-031-75653-5_4
URL	查看原文
文献类型	专著章节
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/500252
专题	生物医学工程学院信息科学与技术学院信息科学与技术学院_博士生生物医学工程学院_PI研究组_赖晓春组
作者单位	1.School of Biomedical Engineering, ShanghaiTech University, Shanghai, China 2.School of Computer Science and Engineering, Southeast University, Nanjing, China 3.School of Information Science and Technology, ShanghaiTech University, Shanghai, China
第一作者单位	生物医学工程学院
推荐引用方式 GB/T 7714	Wenhui, Qin,Zhentao, Liu,Xiaopeng, Yu,et al. Performance Evaluation of Implicit Neural Representations in Diagnostic Fan-Beam CT Imaging. Gewerbestrasse 11, 6330 Cham, Switzerland:Springer, Cham,2024.