title: Sequential Monte Carlo tracking for marginal artery segmentation on CT angiography by multiple cue fusion.
abstract: In this work we formulate vessel segmentation on contrast-enhanced CT angiogram images as a Bayesian tracking problem. To obtain posterior probability estimation of vessel location, we employ sequential Monte Carlo tracking and propose a new vessel segmentation method by fusing multiple cues extracted from CT images. These cues include intensity, vesselness, organ detection, and bridge information for poorly enhanced segments from global path minimization. By fusing local and global information for vessel tracking, we achieved high accuracy and robustness, with significantly improved precision compared to a traditional segmentation method (p = 0.0002). Our method was applied to the segmentation of the marginal artery of the colon, a small bore vessel of potential importance for colon segmentation and CT colonography. Experimental results indicate the effectiveness of the proposed method.
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
authors.forename: Shijun
authors.initials: S
authors.lastname: Wang
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
authors.forename: Brandon
authors.initials: B
authors.lastname: Peplinski
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
authors.forename: Le
authors.initials: L
authors.lastname: Lu
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
authors.forename: Weidong
authors.initials: W
authors.lastname: Zhang
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
authors.forename: Jianfei
authors.initials: J
authors.lastname: Liu
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
authors.forename: Zhuoshi
authors.initials: Z
authors.lastname: Wei
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, 20892-1182, USA.
authors.forename: Ronald M
authors.initials: RM
authors.lastname: Summers
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D001185:Artificial Intelligence; D003106:Colon / Q000098:blood supply*; D003627:Data Interpretation, Statistical; D006801:Humans; D009010:Monte Carlo Method; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*