title: Mapping and characterizing endometrial implants by registering 2D transvaginal ultrasound to 3D pelvic magnetic resonance images.
abstract: We propose a new deformable slice-to-volume registration method to register a 2D Transvaginal Ultrasound (TVUS) to a 3D Magnetic Resonance (MR) volume. Our main goal is to find a cross-section of the MR volume such that the endometrial implants and their depth of infiltration can be mapped from TVUS to MR. The proposed TVUS-MR registration method uses contour to surface correspondences through a novel variational one-step deformable Iterative Closest Point (ICP) method. Specifically, we find a smooth deformation field while establishing point correspondences automatically. We demonstrate the accuracy of the proposed method by quantitative and qualitative tests on both semi-synthetic and clinical data. To generate semi-synthetic data sets, 3D surfaces are deformed with 4-40% degrees of deformation and then various intersection curves are obtained at 0-20° cutting angles. Results show an average mean square error of 5.7934±0.4615mm, average Hausdorff distance of 2.493±0.14mm, and average Dice similarity coefficient of 0.9750±0.0030.
authors.affiliation: Advanced Laparoscopy and Computer Vision (ALCoV) Group, ISIT, Université d'Auvergne and CNRS, France. Electronic address: amir.yavariabdi@gmail.com.
authors.forename: Amir
authors.initials: A
authors.lastname: Yavariabdi
authors.affiliation: Advanced Laparoscopy and Computer Vision (ALCoV) Group, ISIT, Université d'Auvergne and CNRS, France. Electronic address: adrien.bartoli@gmail.com.
authors.forename: Adrien
authors.initials: A
authors.lastname: Bartoli
authors.affiliation: Advanced Laparoscopy and Computer Vision (ALCoV) Group, ISIT, Université d'Auvergne and CNRS, France. Electronic address: chafik.samir@gmail.com.
authors.forename: Chafik
authors.initials: C
authors.lastname: Samir
authors.affiliation: Advanced Laparoscopy and Computer Vision (ALCoV) Group, ISIT, Université d'Auvergne and CNRS, France.
authors.forename: Maxime
authors.initials: M
authors.lastname: Artigues
authors.affiliation: Advanced Laparoscopy and Computer Vision (ALCoV) Group, ISIT, Université d'Auvergne and CNRS, France.
authors.forename: Michel
authors.initials: M
authors.lastname: Canis
mesh_terms: D004715:Endometriosis / Q000175:diagnosis*; D004717:Endometrium / Q000000981:diagnostic imaging* / Q000473:pathology* / Q000601:surgery; D019160:Endosonography / Q000379:methods*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D064847:Multimodal Imaging / Q000379:methods*; D010388:Pelvis / Q000000981:diagnostic imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014621:Vagina / Q000000981:diagnostic imaging
keywords: Endometriosis; Fusion; Iterative closest point; Localization; Multi-modality; Slice-to-volume registration