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Optimization of three‐dimensional angiographic data obtained by self‐calibration of multiview imaging
Author(s) -
Noël Peter B.,
Hoffmann Kenneth R.,
Kasodekar Snehal,
Walczak Alan M.,
Schafer Sebastian
Publication year - 2006
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2350705
Subject(s) - biplane , projection (relational algebra) , translation (biology) , calibration , orientation (vector space) , medical imaging , computer vision , artificial intelligence , computer science , geometry , mathematics , algorithm , biochemistry , chemistry , statistics , messenger rna , engineering , gene , aerospace engineering
Stroke is one of the leading causes of death in the U.S. The treatment of stroke often involves vascular interventions in which devices are guided to the intervention site often through tortuous vessels based on two‐dimensional (2‐D) angiographic images. Three dimensional (3‐D) vascular information may facilitate these procedures. Methods have been proposed for the self‐calibrating determination of 3‐D vessel trees from biplane and multiple plane images and the geometric relationships between the views (imaging geometries). For the biplane analysis, four or more corresponding points must be identified in the biplane images. For the multiple view technique, multiple vessels must be indicated and only the translation vectors relating the geometries are calculated. We have developed methods for the calculation of the 3‐D vessel data and the full transformations relating the multiple views (rotations and translations) obtained during interventional procedures, and the technique does not require indication of corresponding points, but only the indication of a single vessel, e.g., the vessel of interest. Multiple projection views of vessel trees are obtained and transferred to the analysis computer. The vessel or vessels of interest are indicated by the user. Using the initial imaging geometry determined from the gantry information, 3‐D vessel centerlines are calculated using the indicated centerlines in pairs of images. The imaging geometries are then iteratively adjusted and 3‐D centerlines recalculated until the root‐mean‐square (rms) difference between the calculated 3‐D centerlines is minimized. Simulations indicate that the 3‐D centerlines can be accurately determined (to within 1 mm ) even for errors in indication of the vessel endpoints as large as 5 mm . In phantom studies, the average rms difference between the pairwise calculated 3‐D centerlines is approximately 7.5 mm prior to refinement (i.e., using the gantry information alone), whereas the average rms difference is usually below 1 mm after refinement. Accuracies and reliabilities of better than 1 mm were also determined by comparing centerlines determined using multiview and rotational angiography reconstruction and clinical data sets. These results indicate that the multiview approach will provide accurate and reliable 3‐D centerlines for indicated vessel(s) without increasing the dose to the patient.