Integration of Vibro-Acoustography Imaging Modality with the Traditional Mammography

Vibro-acoustography (VA) is a new imaging modality that has been applied to both medical and industrial imaging. Integrating unique diagnostic information of VA with other medical imaging is one of our research interests. In this work, we establish correspondence between the VA images and traditional X-ray mammogram by adopting a flexible control-point selection technique for image registration. A modified second-order polynomial, which simply leads to a scale/rotation/translation invariant registration, was used. The results of registration were used to spatially transform the breast VA images to map with the X-ray mammography with a registration error of less than 1.65 mm. The fused image is defined as a linear integration of the VA and X-ray images. Moreover, a color-based fusion technique was employed to integrate the images for better visualization of structural information

Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction

Traditional geometric registration based estimation methods only exploit the CAD model implicitly, which leads to their dependence on observation quality and deficiency to occlusion. To address the problem,the paper proposes a bidirectional correspondence prediction network with a point-wise attention-aware mechanism. This network not only requires the model points to predict the correspondence but also explicitly models the geometric similarities between observations and the model prior. Our key insight is that the correlations between each model point and scene point provide essential information for learning point-pair matches. To further tackle the correlation noises brought by feature distribution divergence, we design a simple but effective pseudo-siamese network to improve feature homogeneity. Experimental results on the public datasets of LineMOD, YCB-Video, and Occ-LineMOD show that the proposed method achieves better performance than other state-of-the-art methods under the same evaluation criteria. Its robustness in estimating poses is greatly improved, especially in an environment with severe occlusions

Analysis of ICP variants for the registration of partially overlapping time-of-flight range images

The iterative closest point (ICP) algorithm is one of the most commonly used methods for registering partially overlapping range images. Nevertheless, this algorithm was not originally designed for this task, and many variants have been proposed in an effort to improve its prociency. The relatively new full-field amplitude-modulated time-of-flight range imaging cameras present further complications to registration in the form of measurement errors due to mixed and scattered light. This paper investigates the effectiveness of the most common ICP variants applied to range image data acquired from full-field range imaging cameras. The original ICP algorithm combined with boundary rejection performed the same as or better than the majority of variants tested. In fact, many of these variants proved to decrease the registration alignment

Automatic landmark annotation and dense correspondence registration for 3D human facial images

Dense surface registration of three-dimensional (3D) human facial images holds great potential for studies of human trait diversity, disease genetics, and forensics. Non-rigid registration is particularly useful for establishing dense anatomical correspondences between faces. Here we describe a novel non-rigid registration method for fully automatic 3D facial image mapping. This method comprises two steps: first, seventeen facial landmarks are automatically annotated, mainly via PCA-based feature recognition following 3D-to-2D data transformation. Second, an efficient thin-plate spline (TPS) protocol is used to establish the dense anatomical correspondence between facial images, under the guidance of the predefined landmarks. We demonstrate that this method is robust and highly accurate, even for different ethnicities. The average face is calculated for individuals of Han Chinese and Uyghur origins. While fully automatic and computationally efficient, this method enables high-throughput analysis of human facial feature variation.Comment: 33 pages, 6 figures, 1 tabl