Maryam Altalhi, S. Rehman, Fakhre Alam, A. Alarood, A. Rehman, M. Irfan Uddin
{"title":"利用MR和CT三维图像计算主动脉几何形状","authors":"Maryam Altalhi, S. Rehman, Fakhre Alam, A. Alarood, A. Rehman, M. Irfan Uddin","doi":"10.32604/iasc.2022.020607","DOIUrl":null,"url":null,"abstract":"The proper computation of geometric parameters of the aorta and coronary arteries are very important for surgery planning, disease diagnoses, and age-related changes observation in the vessels. The accurate knowledge about the geometry of aorta and coronary arteries is required for the proper investigation of heart related diseases. The geometry of aorta and coronary arteries includes the diameter of the ascending and descending aorta and coronary arteries, length of the coronary arteries, branching angles of the coronary arteries and branching points. These geometric parameters from arteries can be computed from the 3D image data. In this paper, we propose an approach for calculating geometric parameters such as length, diameter of the aorta and angles of the coronary arteries. The proposed method automatically computes the geometry of aorta and left and right coronary arteries. The geometry is computed by logically dividing the aorta, calculating the centerline and extracting the features of aorta and coronary arteries. The method has been tested on different 3D CT/MR image data. The results of the proposed method are tested on different data sets to check its accuracy. The results show more accuracy and less computation time on noisy image data as compared to the already developed method. The obtained results are visualized and compared using visualization toolkit (VTK).","PeriodicalId":50357,"journal":{"name":"Intelligent Automation and Soft Computing","volume":"3 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Computation of Aortic Geometry Using MR and CT 3D Images\",\"authors\":\"Maryam Altalhi, S. Rehman, Fakhre Alam, A. Alarood, A. Rehman, M. Irfan Uddin\",\"doi\":\"10.32604/iasc.2022.020607\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proper computation of geometric parameters of the aorta and coronary arteries are very important for surgery planning, disease diagnoses, and age-related changes observation in the vessels. The accurate knowledge about the geometry of aorta and coronary arteries is required for the proper investigation of heart related diseases. The geometry of aorta and coronary arteries includes the diameter of the ascending and descending aorta and coronary arteries, length of the coronary arteries, branching angles of the coronary arteries and branching points. These geometric parameters from arteries can be computed from the 3D image data. In this paper, we propose an approach for calculating geometric parameters such as length, diameter of the aorta and angles of the coronary arteries. The proposed method automatically computes the geometry of aorta and left and right coronary arteries. The geometry is computed by logically dividing the aorta, calculating the centerline and extracting the features of aorta and coronary arteries. The method has been tested on different 3D CT/MR image data. The results of the proposed method are tested on different data sets to check its accuracy. The results show more accuracy and less computation time on noisy image data as compared to the already developed method. The obtained results are visualized and compared using visualization toolkit (VTK).\",\"PeriodicalId\":50357,\"journal\":{\"name\":\"Intelligent Automation and Soft Computing\",\"volume\":\"3 1\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent Automation and Soft Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.32604/iasc.2022.020607\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Automation and Soft Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.32604/iasc.2022.020607","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}
Computation of Aortic Geometry Using MR and CT 3D Images
The proper computation of geometric parameters of the aorta and coronary arteries are very important for surgery planning, disease diagnoses, and age-related changes observation in the vessels. The accurate knowledge about the geometry of aorta and coronary arteries is required for the proper investigation of heart related diseases. The geometry of aorta and coronary arteries includes the diameter of the ascending and descending aorta and coronary arteries, length of the coronary arteries, branching angles of the coronary arteries and branching points. These geometric parameters from arteries can be computed from the 3D image data. In this paper, we propose an approach for calculating geometric parameters such as length, diameter of the aorta and angles of the coronary arteries. The proposed method automatically computes the geometry of aorta and left and right coronary arteries. The geometry is computed by logically dividing the aorta, calculating the centerline and extracting the features of aorta and coronary arteries. The method has been tested on different 3D CT/MR image data. The results of the proposed method are tested on different data sets to check its accuracy. The results show more accuracy and less computation time on noisy image data as compared to the already developed method. The obtained results are visualized and compared using visualization toolkit (VTK).
期刊介绍:
An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of intelligent automation, artificial intelligence, computer science, control, intelligent data science, modeling and systems engineering. It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence, cyber security and deep learning. It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of systems engineering and soft computing. The journal will publish original and survey papers on artificial intelligence, intelligent automation and computer engineering with an emphasis on current and potential applications of soft computing. It will have a broad interest in all engineering disciplines, computer science, and related technological fields such as medicine, biology operations research, technology management, agriculture and information technology.