1
|
[Nonlocal low-rank and sparse matrix decomposition for low-dose cerebral perfusion CT image restoration]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2022; 42:1309-1316. [PMID: 36210703 PMCID: PMC9550540 DOI: 10.12122/j.issn.1673-4254.2022.09.06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVE To present a nonlocal low-rank and sparse matrix decomposition (NLSMD) method for low-dose cerebral perfusion CT image restoration. METHODS Low-dose cerebral perfusion CT images were first partitioned into a matrix, and the low- rank and sparse matrix decomposition model was constructed to obtain high-quality low-dose cerebral perfusion CT images. The cerebral hemodynamic parameters were calculated from the restored high-quality CT images. RESULTS In the phantom study, the average structured similarity (SSIM) value of the sequential images obtained by filtered back-projection (FBP) algorithm was 0.9438, which was increased to 0.9765 using the proposed algorithm; the SSIM values of cerebral blood flow (CBF) and cerebral blood volume (CBV) map obtained by FBP algorithm were 0.7005 and 0.6856, respectively, which were increased using the proposed algorithm to 0.7871 and 0.7972, respectively. CONCLUSION The proposed method can effectively suppress noises in low-dose cerebral perfusion CT images to obtain accurate cerebral hemodynamic parameters.
Collapse
|
2
|
Zeng D, Zeng C, Zeng Z, Li S, Deng Z, Chen S, Bian Z, Ma J. Basis and current state of computed tomography perfusion imaging: a review. Phys Med Biol 2022; 67. [PMID: 35926503 DOI: 10.1088/1361-6560/ac8717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 08/04/2022] [Indexed: 12/30/2022]
Abstract
Computed tomography perfusion (CTP) is a functional imaging that allows for providing capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we aim to offer insight into CTP imaging which covers the basics and current state of CTP imaging, then summarize the technical applications in the CTP imaging as well as the future technological potential. At first, we focus on the fundamentals of CTP imaging including systematically summarized CTP image acquisition and hemodynamic parameter map estimation techniques. A short assessment is presented to outline the clinical applications with CTP imaging, and then a review of radiation dose effect of the CTP imaging on the different applications is presented. We present a categorized methodology review on known and potential solvable challenges of radiation dose reduction in CTP imaging. To evaluate the quality of CTP images, we list various standardized performance metrics. Moreover, we present a review on the determination of infarct and penumbra. Finally, we reveal the popularity and future trend of CTP imaging.
Collapse
Affiliation(s)
- Dong Zeng
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Cuidie Zeng
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Zhixiong Zeng
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Sui Li
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Zhen Deng
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Sijin Chen
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Zhaoying Bian
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| | - Jianhua Ma
- School of Biomedical Engineering, Southern Medical University, Guangdong 510515, China; and Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangdong 510515, People's Republic of China
| |
Collapse
|
3
|
牛 善, 刘 宏, 刘 沛, 张 梦, 邱 洋, 黎 钰, 谢 国, 刘 国, 卢 绍. [Low-dose cerebral perfusion CT image restoration using prior image constrained diffusion tensor]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2021; 41:1226-1233. [PMID: 34549715 PMCID: PMC8527232 DOI: 10.12122/j.issn.1673-4254.2021.08.15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Indexed: 01/24/2023]
Abstract
OBJECTIVE We propose an efficient method to reduce the noise in low-dose cerebral perfusion CT images using prior image constrained diffusion tensor to reduce the radiation dose in brain CT examination. METHODS By utilizing the redundant information in cerebral perfusion CT images, we embedded the complementary structure information in prior images into lowdose cerebral perfusion CT image restoration process to suppress the image noise and artifacts.We first calculated the diffusion tensor for the low-dose cerebral perfusion CT image and prior image separately and then constructed a prior image constrained diffusion tensor (PICDT) to incorporate the structure information from the prior image into low-dose image restoration process. RESULTS In experiments with the Shepp-Logan phantom, the SSIM value of CBF map obtained by the proposed algorithm was increased by 63% as compared with that of the FBP algorithm.In analysis of the clinical dataset, the SSIM value of CBF map obtained by the proposed algorithm was increased by 45% as compared with that of FBP algorithm. CONCLUSION The proposed method can effectively reduce noises and artifacts of low-dose cerebral perfusion CT images while maintaining the structural details to obtain accurate cerebral hemodynamic maps.
Collapse
Affiliation(s)
- 善洲 牛
- 赣南师范大学数学与计算机科学学院, 江西 赣州 341000School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China
| | - 宏 刘
- 赣南师范大学数学与计算机科学学院, 江西 赣州 341000School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China
| | - 沛沄 刘
- 赣南师范大学数学与计算机科学学院, 江西 赣州 341000School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China
| | - 梦真 张
- 赣南师范大学数学与计算机科学学院, 江西 赣州 341000School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China
| | - 洋 邱
- 赣南师范大学数学与计算机科学学院, 江西 赣州 341000School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China
| | - 钰 黎
- 赣南师范大学数学与计算机科学学院, 江西 赣州 341000School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China
| | - 国强 谢
- 赣南师范大学数学与计算机科学学院, 江西 赣州 341000School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China
| | - 国良 刘
- 赣南医学院医学信息工程学院, 江西 赣州 341000School of Medical Information Engineering of Gannan Medical University, Ganzhou 341000, China
| | - 绍辉 卢
- 赣南医学院第一附属医院, 江西 赣州 341000First Affiliated Hospital of Gannan Medical University, Ganzhou 341000, China
| |
Collapse
|