Complete region of interest reconstruction by fusing multiview deformable three-dimensional transesophageal echocardiography images.

Background: While three-dimensional transesophageal echocardiography (3D TEE) has been increasingly used for assessing cardiac anatomy and function, it still suffers from a limited field of view (FoV) of the ultrasound transducer. Therefore, it is difficult to examine a complete region of interest without moving the transducer. Existing methods extend the FoV of 3D TEE images by mosaicing multiview static images, which requires synchronization between 3D TEE images and electrocardiogram (ECG) signal to avoid deformations in the images and can only get the widened image at a specific phase.

Purpose: This work aims to develop a novel multiview nonrigid registration and fusion method to extend the FoV of 3D TEE images at different cardiac phases, avoiding the bias toward the specifically chosen phase.

Methods: A multiview nonrigid registration and fusion method is proposed to enlarge the FoV of 3D TEE images by fusing dynamic images captured from different viewpoints sequentially. The deformation field for registering images is defined by a collection of affine transformations organized in a graph structure and is estimated by a direct (intensity-based) method. The accuracy of the proposed method is evaluated by comparing it with two B-spline-based methods, two Demons-based methods, and one learning-based method VoxelMorph. Twenty-nine sequences of in vivo 3D TEE images captured from four patients are used for the comparative experiments. Four performance metrics including checkerboard volumes, signed distance, mean absolute distance (MAD), and Dice similarity coefficient (DSC) are used jointly to evaluate the accuracy of the results. Additionally, paired t-tests are performed to examine the significance of the results.

Results: The qualitative results show that the proposed method can align images more accurately and obtain the fused images with higher quality than the other five methods. Additionally, in the evaluation of the segmented left atrium (LA) walls for the pairwise registration and sequential fusion experiments, the proposed method achieves the MAD of (0.07 ± 0.03) mm for pairwise registration and (0.19 ± 0.02) mm for sequential fusion. Paired t-tests indicate that the results obtained from the proposed method are more accurate than those obtained by the state-of-the-art VoxelMorph and the diffeomorphic Demons methods at the significance level of 0.05. In the evaluation of left ventricle (LV) segmentations for the sequential fusion experiments, the proposed method achieves a DSC of (0.88 ± 0.08), which is also significantly better than diffeomorphic Demons at the 0.05 level. The FoVs of the final fused 3D TEE images obtained by our method are enlarged around two times compared with the original images.

Conclusions: Without selecting the static (ECG-gated) images from the same cardiac phase, this work addressed the problem of limited FoV of 3D TEE images in the deformable scenario, obtaining the fused images with high accuracy and good quality. The proposed method could provide an alternative to the conventional fusion methods that are biased toward the specifically chosen phase.