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Registration between the intraoperative 2D digital subtraction angiography (DSA) and the pre-operative 3D computed tomography angiography (CTA) is useful in the guidance of vascular interventional surgery (VIS). Because of the flow and diffusion of contrast in vessels, not all the vessels are visible in the DSA, which leads to difficulty in registration. Although the conventional mutual information (MI) and the normalized MI (NMI) perform well in orthopedic surgery, it cannot perform as well in VIS because of the missing vessel in DSA. In this paper, a novel similarity measure, WLMI (Weighted Local Mutual Information), is proposed to perform 2D-3D registration, which uses the patches selected in DSA to find the best match in the DRRs (digital radiography reconstruction) with weighted MI. At first, we choose several ways to measure the richness of block information to select small and scattered patches in the DSA image. Subsequently, different weights are assigned to these patches according to their information abundance by calculating the local MI. With the proposed WLMI, the 2D-3D registration experiments are conducted with the synthetic and real DSA images to CTA vessel model. In synthetic registration, the optimal way to measure information abundance and the optimal weight parameter value are selected. The registration with intact and partially absent vessels are compared with the conventional methods using MAE, mTREproj, and IoU metrics. In the registration of real DSA to CTA model, only IoU is used to compare the difference since the ground-truth cannot be derived. In synthetic registration with vessel excalation test, the mTREproj is 2.9 mm and the IoU is 96.7%. In a real registration test, the IoU reaches 81.3%. Both the synthetic and real DSA registration results show that the proposed WLMI can cope with the problem that partial vessel is invisible in the DSA, and outperformed the conventional methods such as MI and NMI. Therefore, the WLMI is more suitable to be used in the 2D/3D registration task in VIS.

2D-3D Registration With Weighted Local Mutual Information in Vascular Interventions