title: Automatic Lumen Segmentation in Intravascular Optical Coherence Tomography Images Using Level Set.
abstract: Automatic lumen segmentation from intravascular optical coherence tomography (IVOCT) images is an important and fundamental work for diagnosis and treatment of coronary artery disease. However, it is a very challenging task due to irregular lumen caused by unstable plaque and bifurcation vessel, guide wire shadow, and blood artifacts. To address these problems, this paper presents a novel automatic level set based segmentation algorithm which is very competent for irregular lumen challenge. Before applying the level set model, a narrow image smooth filter is proposed to reduce the effect of artifacts and prevent the leakage of level set meanwhile. Moreover, a divide-and-conquer strategy is proposed to deal with the guide wire shadow. With our proposed method, the influence of irregular lumen, guide wire shadow, and blood artifacts can be appreciably reduced. Finally, the experimental results showed that the proposed method is robust and accurate by evaluating 880 images from 5 different patients and the average DSC value was 98.1% ± 1.1%.
authors.affiliation: The State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi 710119, China; School of the Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China; University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Yihui
authors.identifier: 0000-0001-5786-4959
authors.initials: Y
authors.lastname: Cao
authors.affiliation: Department of Cardiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
authors.forename: Kang
authors.initials: K
authors.lastname: Cheng
authors.affiliation: Department of Aerospace Biodynamics, Fourth Military Medical University, Xi'an, Shaanxi 710032, China; Xidian University, Xi'an, Shaanxi 710071, China.
authors.forename: Xianjing
authors.initials: X
authors.lastname: Qin
authors.affiliation: School of the Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
authors.forename: Qinye
authors.initials: Q
authors.lastname: Yin
authors.affiliation: The State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi 710119, China.
authors.forename: Jianan
authors.initials: J
authors.lastname: Li
authors.affiliation: The State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi 710119, China.
authors.forename: Rui
authors.identifier: 0000-0002-1069-9359
authors.initials: R
authors.lastname: Zhu
authors.affiliation: The State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi 710119, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D003331:Coronary Vessels; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional; D058226:Plaque, Atherosclerotic / Q000000981:diagnostic imaging; D041623:Tomography, Optical Coherence / Q000379:methods*