3D-2D Registration Based on Mesh-Derived Image Bisection

Thivierge-Gaulin, David; Chou, Chen-Rui; Kiraly, Atilla P.; Chefd’hotel, Christophe; Strobel, Norbert; Cheriet, Foued

doi:10.1007/978-3-642-31340-0_8

Cited by 7 publications

(9 citation statements)

References 6 publications

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“…The overall interuser variability observed in the manual registrations was 3.2 ± 2.3 mm. Considering all sequences, ρ CADE performed significantly better than ρ shad thr , ρ shad DSA , and the state-of-the-art method by Thivierge-Gaulin et al [ 16 ]. Although ρ edge gave significantly worse results than all other measures, a combination with ρ edge could improve the results of ρ shad thr and ρ shad DSA significantly.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…A previous approach [ 16 ] tried to find a transformation T of the 3D model such that the projected shadows S T A , S T B of the model into the A-plane and the B-plane of a biplane C-arm system fit best to the contrasted region. Using the normalized cross-correlation (NCC), denoted as ρ n , of two images I 1 , I 2 with corresponding mean values μ 1 , μ 2 and standard deviations σ 1 , σ 2

the similarity of the projected shadow and I DSA can be measured.…”

Section: Registration Methodsmentioning

confidence: 99%

“…Previous approaches [ 16 , 17 ] for LA registration searched for a rigid transformation of the LA such that either its projected shadow or its DRR fit to the contrasted area in both fluoroscopic images. 3D information was taken into account insofar as the resulting projections came from the same 3D position of the model.…”

Section: Registration Methodsmentioning

confidence: 99%

“…Currently, very few publications deal with registration based on contrast agent: In a first approach towards automatic LA registration, Thivierge-Gaulin et al [ 16 ] tried to find a 3D pose of a model such that its projected shadow matches the contrasted area in a selected image, enhanced by digital subtraction angiography (DSA), best. However, if only a small amount of contrast agent is injected into a somewhat large chamber such as the left atrium, this approach will not lead to a distinct optimum, because the anatomy may not be fully opacified.…”

Section: Introductionmentioning

confidence: 99%

“…In Section 3 , we evaluate a similarity measure based on the projected shadow which is close to the approach by Thivierge-Gaulin et al [ 16 ] and the two new methods as well as combinations of them. The results are discussed in Section 4 .…”

Section: Introductionmentioning

confidence: 99%

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Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent

Hoffmann

Kowalewski

Maier

et al. 2016

International Journal of Biomedical Imaging

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For augmented fluoroscopy during cardiac ablation, a preoperatively acquired 3D model of a patient's left atrium (LA) can be registered to X-ray images recorded during a contrast agent (CA) injection. An automatic registration method that works also for small amounts of CA is desired. We propose two similarity measures: The first focuses on edges of the patient anatomy. The second computes a contrast agent distribution estimate (CADE) inside the 3D model and rates its consistency with the CA as seen in biplane fluoroscopic images. Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. For well-contrasted sequences, the error for all 73 frames was 7.9 ± 6.3 mm and it dropped to 4.6 ± 4.0 mm when registering to an automatically selected, well enhanced frame in each sequence. Temporal filtering reduced the error for all frames from 7.9 ± 6.3 mm to 5.7 ± 4.6 mm. The error was typically higher if less CA was used. A combination of both similarity measures outperforms a previously proposed similarity measure. The mean accuracy for well contrasted sequences is in the range of other proposed manual registration methods.

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Section: Experiments and Resultsmentioning

confidence: 99%

the similarity of the projected shadow and I DSA can be measured.…”

Section: Registration Methodsmentioning

confidence: 99%