Template‐based CTA to x‐ray angio rigid registration of coronary arteries in frequency domain with automatic x‐ray segmentation. Issue 10 (11th September 2013)

• Record Type: Journal Article
• Authors: Aksoy, Timur; Unal, Gozde; Demirci, Stefanie; Navab, Nassir; Degertekin, Muzaffer
• Is Part Of: Medical physics. Volume 40:Issue 10(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-09-11
• Subjects: Angiography -- Registration -- Segmentation -- Computed tomography -- Fluoroscopy -- Numerical optimization; blood vessels -- cameras -- computerised tomography -- diagnostic radiography -- Fourier transforms -- image motion analysis -- image reconstruction -- image registration -- image segmentation -- medical image processing -- numerical analysis -- optimisation -- phantoms; 3D‐2D rigid registration -- data integration for the clinic/OR -- image‐guided therapy -- C‐arm angiography intervention -- CTA to x‐ray registration; Computerised tomographs -- Biological material, e.g. blood, urine; Haemocytometers -- Details of cameras or camera bodies; Accessories therefor -- Cameras -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Analysis of motion -- Transforming light or analogous information into electric information; Medical imaging -- Medical X‐ray imaging -- X‐ray imaging -- Digital radiography -- Vascular system -- Angiography -- X‐ray optics -- Rotation measurement -- Medical image segmentation -- Fourier transforms; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4819938
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : A key challenge for image guided coronary interventions is accurate and absolutely robust image registration bringing together preinterventional information extracted from a three‐dimensional (3D) patient scan and live interventional image information. In this paper, the authors present a novel scheme for 3D to two‐dimensional (2D) rigid registration of coronary arteries extracted from preoperative image scan (3D) and a single segmented intraoperative x‐ray angio frame in frequency and spatial domains for real‐time angiography interventions by C‐arm fluoroscopy. Methods: : Most existing rigid registration approaches require a close initialization due to the abundance of local minima and high complexity of search algorithms. The authorsˈ method eliminates this requirement by transforming the projections into translation‐invariant Fourier domain for estimating the 3D pose. For 3D rotation recovery, template Digitally Reconstructed Radiographs (DRR) as candidate poses of 3D vessels of segmented computed tomography angiography are produced by rotating the camera (image intensifier) around the DICOM angle values with a specific range as in C‐arm setup. The authors have compared the 3D poses of template DRRs with the segmented x‐ray after equalizing the scales in three domains, namely, Fourier magnitude, Fourier phase, and Fourier polar. The best rotation pose candidate was chosen by one of the highest similarity measures returned by the methods in these domains. It has been noted in literature that frequency domain methods are robust against noise and occlusion which was also validated by the authorsˈ results. 3D translation of the volume was then recovered by distance‐map based BFGS optimization well suited to convex structure of the authorsˈ objective function without local minima due to distance maps. A novel automatic x‐ray vessel segmentation was also performed in this study. Results: : Final results were evaluated in 2D projection space for patient data; and with ground truth values and landmark distances for the images acquired with a solid phantom vessel. Results validate that rotation recovery in frequency domain is robust against differences in segmentations in two modalities. Distance‐map translation is successful in aligning coronary trees with highest possible overlap. Conclusions: : Numerical and qualitative results show that single view rigid alignment in projection space is successful. This work can be extended with multiple views to resolve depth ambiguity and with deformable registration to account for nonrigid motion in patient data.