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Xu B, Wang L, Yang J, Yang B, Xu L, Chen Y, Zheng D. Multi-constraint point set registration with redundant point removal for the registration of coronary arteries. Comput Biol Med 2023; 165:107438. [PMID: 37688990 DOI: 10.1016/j.compbiomed.2023.107438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 08/06/2023] [Accepted: 08/29/2023] [Indexed: 09/11/2023]
Abstract
BACKGROUND Coronary artery disease (CAD) is the leading cause of death worldwide. The registration of the coronary artery at different phases can help radiologists explore the motion patterns of the coronary artery and assist in the diagnosis of CAD. However, there is no automatic and easy-to-execute method to solve the missing data problem that occurs at the endpoints of the coronary artery tree. This paper proposed a non-rigid multi-constraint point set registration with redundant point removal (MPSR-RPR) algorithm to tackle this challenge. METHODS Firstly, the MPSR-RPR algorithm roughly registered two coronary artery point sets with the pre-set smoothness regularization parameter and Gaussian filter width value. The moving coherent, local feature, and the corresponding relationship between bifurcation point pairs were exploited as the constraints. Next, the spatial geometry information of the coronary artery was utilized to automatically recognize the vessel endpoints and to delete the redundant points of the coronary artery. Finally, the algorithm continued carrying out the multi-constraint registration with another group of the pre-set parameters to improve the alignment performance. RESULTS The experimental results demonstrated that the MPSR-RPR algorithm achieved a significantly lower mean value of the modified Hausdorff distance (MHD) compared to the other state-of-the-art methods for addressing the serious missing data in the left and right coronary arteries. CONCLUSION This study demonstrated the effectiveness of the proposed algorithm in aligning coronary arteries, providing significant value in assisting in the diagnosis of coronary artery and myocardial lesions.
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Affiliation(s)
- Bu Xu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China
| | - Lu Wang
- School of Computer Science and Engineering, Northeastern University, Shenyang, 110169, China
| | - Jinzhong Yang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China
| | - Benqiang Yang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China; Department of Radiology, General Hospital of North Theater Command, Shenyang, 110016, China
| | - Lisheng Xu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China; Key Laboratory of Medical Image Computing, Ministry of Education, Shenyang, 110169, China; Engineering Research Center of Medical Imaging and Intelligent Analysis, Ministry of Education, Shenyang, 110169, China.
| | - Yang Chen
- School of Computer Science and Engineering, Southeast University, Nanjing, 210096, China
| | - Dingchang Zheng
- Research Centre of Intelligent Healthcare, Coventry University, Coventry, CV1 5RW, United Kingdom
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Estimation of coronary artery movement using a non-rigid registration with global-local structure preservation. Comput Biol Med 2021; 141:105125. [PMID: 34952339 DOI: 10.1016/j.compbiomed.2021.105125] [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: 06/15/2021] [Revised: 12/05/2021] [Accepted: 12/05/2021] [Indexed: 11/20/2022]
Abstract
BACKGROUND At present, coronary artery disease (CAD) is the leading cause of death worldwide. Many studies have shown that CAD is strongly associated with the motion characteristics of the coronary arteries. Although cardiovascular imaging technology has been widely used for the diagnosis of CAD, the motion parameters of the heart and coronary arteries cannot be directly calculated from the images. In this paper, we propose a point set registration method with global and local topology constraints to quantify coronary artery movement. METHODS The global constraint is the motion coherence of the point set which enforces the smoothness of the displacement field. The local linear embedding based topological structure and the local feature descriptor i.e., the 3D shape context, are designed to retain the local structure of the point set. We incorporate these constraints into a maximum likelihood framework and derive an expectation-maximization algorithm to obtain the transformation function between the two point sets. The proposed method was compared with four existing algorithms using simulated data and applied to the real data obtained from 4D CT angiograms. RESULTS For the simulation data, the proposed method achieves a lower registration error than the comparison algorithms. For the real data, the proposed method shows that, in most cases, the right coronary artery achieves a larger velocity than the left anterior descending and left circumflex branches, and there are three well-defined velocity peaks, during the cardiac cycle for these branches. CONCLUSION The proposed approach is feasible and effective in quantifying coronary artery movement and thus adds to the diagnostic power of coronary imaging.
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Yang G, Lv T, Shen Y, Li S, Yang J, Chen Y, Shu H, Luo L, Coatrieux JL. Vessel Structure Extraction using Constrained Minimal Path Propagation. Artif Intell Med 2020; 105:101846. [PMID: 32505425 DOI: 10.1016/j.artmed.2020.101846] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 10/23/2019] [Accepted: 03/20/2020] [Indexed: 11/18/2022]
Abstract
Minimal path method has been widely recognized as an efficient tool for extracting vascular structures in medical imaging. In a previous paper, a method termed minimal path propagation with backtracking (MPP-BT) was derived to deal with curve-like structures such as vessel centerlines. A robust approach termed CMPP (constrained minimal path propagation) is here proposed to extend this work. The proposed method utilizes another minimal path propagation procedure to extract the complete vessel lumen after the centerlines have been found. Moreover, a process named local MPP-BT is applied to handle structure missing caused by the so-called close loop problems. This approach is fast and unsupervised with only one roughly set start point required in the whole process to get the entire vascular structure. A variety of datasets, including 2D cardiac angiography, 2D retinal images and 3D kidney CT angiography, are used for validation. A quantitative evaluation, together with a comparison to recently reported methods, is performed on retinal images for which a ground truth is available. The proposed method leads to specificity (Sp) and sensitivity (Se) values equal to 0.9750 and 0.6591. This evaluation is also extended to 3D synthetic vascular datasets and shows that the specificity (Sp) and sensitivity (Se) values are higher than 0.99. Parameter setting and computation cost are analyzed in this paper.
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Affiliation(s)
- Guanyu Yang
- Laboratory of Image Science and Technology, Southeast University, Nanjing, China; Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France; Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China
| | - Tianling Lv
- Laboratory of Image Science and Technology, Southeast University, Nanjing, China; Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China
| | - Yunpeng Shen
- Laboratory of Image Science and Technology, Southeast University, Nanjing, China
| | - Shuo Li
- Department of Medical Imaging, Western University, London, ON, Canada; Digital Image Group of London, London, ON, Canada
| | - Jian Yang
- Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education, China.
| | - Yang Chen
- Laboratory of Image Science and Technology, Southeast University, Nanjing, China; Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France; Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China.
| | - Huazhong Shu
- Laboratory of Image Science and Technology, Southeast University, Nanjing, China; Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France; Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China
| | - Limin Luo
- Laboratory of Image Science and Technology, Southeast University, Nanjing, China; Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France; Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 210096, China
| | - Jean-Louis Coatrieux
- Centre de Recherche en Information Biomedicale Sino-Francais (LIA CRIBs), Rennes, France
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Zhang D, Sun S, Wu Z, Chen BJ, Chen T. Vessel tree tracking in angiographic sequences. J Med Imaging (Bellingham) 2017; 4:025001. [PMID: 28413808 PMCID: PMC5385468 DOI: 10.1117/1.jmi.4.2.025001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 03/21/2017] [Indexed: 11/14/2022] Open
Abstract
We present a method to track vessels in angiography [contrast filled vessels in two-dimensional (2-D) x-ray fluoroscopy]. Finding correspondence of a vessel tree from consecutive angiogram frames provides significant value in computer-aided clinical applications such as fast vessel tree segmentation, three-dimensional (3-D) vessel topology reconstruction from corresponding centerlines, cardiac motion understanding, etc. However, establishing an accurate vessel tree correspondence (vessel tree tracking) is a nontrivial problem due to nonlinear periodic cardiac and breathing motion in 2-D views, foreshortening, false bifurcations due to 3-D to 2-D projection, occlusion from other anatomies, etc. The vessel tree is represented by BSpline curves. The control points of the BSpline curves are landmarks that are the tracking targets. Our method maximizes the appearance similarity while preserving the vessel structure. A directed acyclic graph (DAG) is employed to represent the appearance and shape structure of the vessel tree: nodes from the DAG encode the appearance of the vessel tree landmarks, and the edges encode the relative locations between landmarks. The vessel tree tracking problem turns into finding the most similar tree from the DAG in the next frame, and it is solved using an efficient dynamic programming algorithm. We performed evaluations on 62 x-ray angiography sequences (above 1000 frames). Experiment results show our algorithm is robust to these challenges and delivers better performance, compared to four existing methods.
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Affiliation(s)
- Dong Zhang
- Siemens Healthcare, Medical Imaging Technologies, Princeton, New Jersey, United States
| | - Shanhui Sun
- Siemens Healthcare, Medical Imaging Technologies, Princeton, New Jersey, United States
| | - Ziyan Wu
- Siemens Corporation, Corporate Technology, Princeton, New Jersey, United States
| | - Bor-Jeng Chen
- Siemens Healthcare, Medical Imaging Technologies, Princeton, New Jersey, United States
| | - Terrence Chen
- Siemens Healthcare, Medical Imaging Technologies, Princeton, New Jersey, United States
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Chen Y, Zhang Y, Yang J, Cao Q, Yang G, Chen J, Shu H, Luo L, Coatrieux JL, Feng Q. Curve-Like Structure Extraction Using Minimal Path Propagation With Backtracking. IEEE TRANSACTIONS ON IMAGE PROCESSING : A PUBLICATION OF THE IEEE SIGNAL PROCESSING SOCIETY 2016; 25:988-1003. [PMID: 26552086 DOI: 10.1109/tip.2015.2496279] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Minimal path techniques can efficiently extract geometrically curve-like structures by finding the path with minimal accumulated cost between two given endpoints. Though having found wide practical applications (e.g., line identification, crack detection, and vascular centerline extraction), minimal path techniques suffer from some notable problems. The first one is that they require setting two endpoints for each line to be extracted (endpoint problem). The second one is that the connection might fail when the geodesic distance between the two points is much shorter than the desirable minimal path (shortcut problem). In addition, when connecting two distant points, the minimal path connection might become inefficient as the accumulated cost increases over the propagation and results in leakage into some non-feature regions near the starting point (accumulation problem). To address these problems, this paper proposes an approach termed minimal path propagation with backtracking. We found that the information in the process of backtracking from reached points can be well utilized to overcome the above problems and improve the extraction performance. The whole algorithm is robust to parameter setting and allows a coarse setting of the starting point. Extensive experiments with both simulated and realistic data are performed to validate the performance of the proposed method.
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Cong W, Yang J, Ai D, Chen Y, Liu Y, Wang Y. Quantitative Analysis of Deformable Model-Based 3-D Reconstruction of Coronary Artery From Multiple Angiograms. IEEE Trans Biomed Eng 2015; 62:2079-90. [DOI: 10.1109/tbme.2015.2408633] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Yang G, Hu Y, Huang X, Shu H, Toumoulin C. Simulation environment of X-ray rotational angiography using 3D+t coronary tree model. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2012; 2012:629-632. [PMID: 23365971 DOI: 10.1109/embc.2012.6346010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
The newly introduced cardiac rotational angiography (RA) can provide a large amount of projections from different angles which greatly improve the 3D coronary tree reconstruction. However, the reconstruction methods are difficult to be objectively evaluated due to the complicated topology of coronary tree and non-linear cardiac motion. In this paper, we present a simulation environment of rotational angiography acquisition system to facilitate the improvements and the evaluations of reconstruction algorithms. A 3D+t coronary tree model reconstructed from MSCT sequence is employed to enhance the reality of simulation. A simulation environment of X-ray coronary angiography is developed based on distance-driven projection algorithm. The static angiography is firstly simulated to verify the dynamic model by comparing the displacements of landmarks with the real static angiography of the same patient. Rotational simulation results are then obtained with real system parameters to provide a complete and true-to-life RA sequence representing the morphology of moving coronary tree.
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Affiliation(s)
- Guanyu Yang
- Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, 210096, Nanjing, China.
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