DSR: Direct Simultaneous Registration for Multiple 3D Images
This work addresses the challenge of 3D image registration in scenarios like Transesophageal Echocardiography where distinct features are unavailable, offering an incremental improvement over existing methods.
The paper tackles the problem of registering multiple 3D images without needing a reference image or feature extraction, by proposing the Direct Simultaneous Registration (DSR) algorithm, which optimizes global poses by maximizing similarity to a panoramic image and is shown to outperform four existing methods in accuracy while using fewer computational resources than the state-of-the-art APE method.
This paper presents a novel algorithm named Direct Simultaneous Registration (DSR) that registers a collection of 3D images in a simultaneous fashion without specifying any reference image, feature extraction and matching, or information loss or reuse. The algorithm optimizes the global poses of local image frames by maximizing the similarity between a predefined panoramic image and local images. Although we formulate the problem as a Direct Bundle Adjustment (DBA) that jointly optimizes the poses of local frames and the intensities of the panoramic image, by investigating the independence of pose estimation from the panoramic image in the solving process, DSR is proposed to solve the poses only and proved to be able to obtain the same optimal poses as DBA. The proposed method is particularly suitable for the scenarios where distinct features are not available, such as Transesophageal Echocardiography (TEE) images. DSR is evaluated by comparing it with four widely used methods via simulated and in-vivo 3D TEE images. It is shown that the proposed method outperforms these four methods in terms of accuracy and requires much fewer computational resources than the state-of-the-art accumulated pairwise estimates (APE).