Machine precision assessment in 3D/2D digital subtracted angiography image registration

Erwan Kerrien; Regis Vaillant; Laurent Launay; Marie-Odile Berger; Eric Maurincomme; Luc Picard

doi:10.1117/12.310906

24 June 1998 Machine precision assessment in 3D/2D digital subtracted angiography image registration

Erwan Kerrien, Regis Vaillant, Laurent Launay, Marie-Odile Berger, Eric Maurincomme, Luc Picard

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310906
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

During an interventional neuroradiology exam, knowing the exact location of the catheter tip with respect to the patient can dramatically help the physician. An image registration between digital subtracted angiography (DSA) images and a volumic pre-operative image (magnetic resonance or computed tomography volumes) is a way to infer this important information. This mono-patient multimodality matching can be reduced to finding the projection matrix that transforms any voxel of the volume onto the DSA image plane. This modelization is unfortunately not valid in the case of distorted images, which is the case for DSA images. A classical angiography room can now generate 3D X-ray angiography volumes (3DXA). Since the DSA images are obtained with the same machine, it should be possible to deduce the projection matrix from the sensor data indicating the current machine position. We propose an interpolation scheme, associated to a pre-operative calibration of the machine that allows us to correct the distortions in the image at any position used during the exam with a precision of one pixel. Thereafter, we describe some calibration procedures and an associated model of the machine that can provide us with a projection matrix at any position of the machine. Thus, we obtain a machine-based 2D DSA/3DXA registration. The misregistration error can be limited to 2.5 mm if the patient is well centered within the system. This error is confirmed by a validation on a phantom of the vascular tree. This validation also yields that the residual error is a translation in the 3D space. As a consequence, the registration method presented in this paper can be used as an initial guess to an iterative refining algorithm.

Citation Download Citation

Erwan Kerrien, Regis Vaillant, Laurent Launay, Marie-Odile Berger, Eric Maurincomme, and Luc Picard "Machine precision assessment in 3D/2D digital subtracted angiography image registration", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310906

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