Anatomical image-based rigid registration between fluoroscopic X-ray and CT: methods comparison and experimental results

Joskowicz, Leo; Knaan, Dotan; Livyatan, H.; Yaniv, Ziv; Khoury, Amal; Mosheiff, Rami; Liebergall, Meir

doi:10.1016/s0531-5131(03)00244-9

Cited by 3 publications

(2 citation statements)

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“…Generation of digitally reconstructed radiographs DRRs are synthetic 2D images that simulate real fluoroscopic X-ray images. Most works have created DRRs from CT images by various volume rendering methods [2,22]. In our case, a CT image of the patient is not available.…”

Section: Distortion Correction and Camera Calibrationmentioning

confidence: 99%

“…In this approach, the patient anatomy is captured by a set of calibrated 2D X-ray images, which are then registered to a 3D anatomical model. Image-based registration does not necessitate exposure of the bone of interest, however if the target application requires real-time tracking, then the bone of interest needs to be exposed minimally and affixed with a tracking marker [2].…”

Section: Introductionmentioning

confidence: 99%

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Registration of a CT-like atlas to fluoroscopic X-ray images using intensity correspondences

Hurvitz

Joskowicz

2008

Int J CARS

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Objective We present a novel method for intraoperative image-based bone surface reconstruction and its validation. Materials and methods In the preoperative stage, we construct a CT-like intensity atlas of the anatomy of interest. In the intraoperative stage, we deformably register this atlas to fluoroscopic X-ray images of the patient anatomy. We iteratively refine the atlas-to-patient registration by establishing explicit correspondences between bone surfaces in the atlas and their projections in the X-ray images. The advantage of our method is its use of CT-quality intensity data for correspondence establishment, which eliminates the edgedetection problem and diminishes the miscorrespondence problem. We validate our method on two datasets: (1) an in vitro dry femur; (2) Digitally Reconstructed Radiographs, which were generated from 17 clinical CTs, and simulate realistic in vivo femurs. Results The mean surface approximation error of our femur atlas was 0.85 ± 0.16 mm. On Digitally Reconstructed Radiographs, the mean surface reconstruction error was 1.40 ± 0.55 mm. On a dry femur, the mean surface reconstruction error was 1.44 mm. Conclusion The results show that our reconstruction method is on par with the state of the art in reconstruction of ex vivo femurs. In addition, the results demonstrate that our method is effective in realistic simulations of the in vivo scenario.

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Section: Distortion Correction and Camera Calibrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%