Gal Hayam

Apparatus, method, and computer software product for registration of images of an organ using anatomical features outside the organ

A method for imaging includes receiving a first three-dimensional (3D) image of a vicinity of an organ within a body of a subject and creating a geometrical model of a tubular structure in the first 3D image in the vicinity of the organ. An invasive probe is inserted into the organ, and a second 3D image containing the organ is captured using the invasive probe. One or more points are located on a surface of the tubular structure using the invasive probe, and the second 3D image is registered with the first 3D image by matching the one or more points to the geometrical model.

Registration of high-resolution 3D atrial images with electroanatomical cardiac mapping: evaluation of registration methodology

Registration of atrial high-resolution CT and MR images with a cardiac mapping system can provide real-time electrical activation information, catheter tracking, and recording of lesion position. The cardiac mapping and navigation system comprises a miniature passive magnetic field sensor, an external ultralow magnetic field emitter (location pad), and a processing unit (CARTO, BiosenseWebster). We developed a progressive methodology for both interactively and automatically registering high-resolution 3D atrial images (MR or CT) with the corresponding electrophysiological (EP) points of 3D electro-anatomical (EA) maps. This methodology consists of four types of registration algorithms ranging from landmark-based to surface-based registration. We evaluated the methodology through phantom and patient studies. In the phantom study, we obtain a CT scan of a transparent heart phantom, and then use the CARTO system to visually pick a number of points inside the transparent phantom. After segmenting the atrium into a 3D surface, we register it to the measured EA map. The results are compared to the manual EA point measurements. In the 13-patient study, the four types of registrations are evaluated: visual alignment, landmark registration (three EA points are used), surface-based registration (all EA points are used), and local surface-based registration (a subset of the EA points is used, and one specific point is given a higher weight for a better “local registration”). Surface-based registration proves to be clearly superior to visual alignment. This new registration methodology may help in creating a novel and more visually interactive workflow for EP procedures, with more accurate EA map acquisitions. This may improve the ablation accuracy in atrial fibrillation (AFib) procedures, decrease the dependency on fluoroscopy, and also lead to less radiation delivered to the patient.