title: Vision-based endoscope tracking for 3D ultrasound image-guided surgical navigation.
abstract: This work introduces a self-contained framework for endoscopic camera tracking by combining 3D ultrasonography with endoscopy. The approach can be readily incorporated into surgical workflows without installing external tracking devices. By fusing the ultrasound-constructed scene geometry with endoscopic vision, this integrated approach addresses issues related to initialization, scale ambiguity, and interest point inadequacy that may be faced by conventional vision-based approaches when applied to fetoscopic procedures. Vision-based pose estimations were demonstrated by phantom and ex vivo monkey placenta imaging. The potential contribution of this method may extend beyond fetoscopic procedures to include general augmented reality applications in minimally invasive procedures.
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan. Electronic address: yl.liangjing@gmail.com.
authors.forename: L
authors.initials: L
authors.lastname: Yang
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
authors.forename: J
authors.initials: J
authors.lastname: Wang
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
authors.forename: T
authors.initials: T
authors.lastname: Ando
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
authors.forename: A
authors.initials: A
authors.lastname: Kubota
authors.affiliation: Clinical Research Center, National Center for Child Health and Development, Tokyo, Japan.
authors.forename: H
authors.initials: H
authors.lastname: Yamashita
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
authors.forename: I
authors.initials: I
authors.lastname: Sakuma
authors.affiliation: Clinical Research Center, National Center for Child Health and Development, Tokyo, Japan.
authors.forename: T
authors.initials: T
authors.lastname: Chiba
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
authors.forename: E
authors.initials: E
authors.lastname: Kobayashi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005332:Fetoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*; D016216:Ultrasonography, Prenatal / Q000379:methods*; D014584:User-Computer Interface
keywords: Endoscopy; Minimally invasive fetal surgery; Surgical navigation; Ultrasound imaging; Vision-based tracking