Feature-based non-rigid volume registration of serial coronary CT angiography

Coronary CT angiography (CTA) with multi-slice helical scanners is becoming the integral part of major diagnostic pathways for coronary artery disease. In addition, coronary CTA has demonstrated substantial potential in quantitative coronary plaque characterization. If serial comparisons of plaque progression or regression are to be made, accurate 3D volume registration of these volumes would be particularly useful. In this work, we propose a coronary CTA volume registration of the paired coronary CTA scans using feature-based non-rigid volume registration. We achieve this with a combined registration strategy, which uses the global rigid registration as an initialization, followed by local registration using non-rigid volume registration with a volume preserving constraint. We exploit the extracted coronary trees to help localize and emphasize the region of interest as unnecessary regions hinder registration process, which results in wrong registration result. The extracted binary masks of each coronary tree may not be the same due to initial segmentation errors, which could lead to subsequent bias in the registration process. Therefore we utilize a blur mask which is generated by convolving the Gaussian function with the binary coronary tree mask to include the neighboring vessel region into account. A volume preserving constraint is imposed so that the total volume of the binary mask before and after co-registration remains constant. To validate the proposed method, we perform experiments with data from 3 patients with available serial CT scans (6 scans in total) and measure the distance of anatomical landmarks between the registered serial scans of the same patient.