The reconstruction of complex targets using terahertz technology is often hindered by diffraction and interference of electromagnetic waves, leading to the loss of fine target details. In this research article, we have introduced a terahertz synthetic aperture radar (SAR) imaging method that integrates an iterative closest point (ICP) algorithm, referred to as SAR-ICP, to achieve accurate reconstruction of intricate target structures. To accomplish this, multiple sets of point cloud data are acquired by varying the illumination viewpoint. The ICP algorithm is then employed to align and fuse these datasets, resulting in the generation of high-quality three-dimensional (3D) images. The experimental results validate the effectiveness of the proposed SAR-ICP method. The information entropy of the reconstructed 3D image using the SAR-ICP is approximately 0.05 times that of the conventional SAR method, indicating a superior image quality. In the future, we anticipate the widespread application of this method in areas such as security inspection, non-destructive testing, and other complex scenarios.
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http://dx.doi.org/10.1364/AO.495260 | DOI Listing |
Int J Comput Assist Radiol Surg
March 2025
Department of Radiology & Nuclear Medicine, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands.
Purpose: In augmented reality (AR) surgical navigation, a registration step is required to align the preoperative data with the patient. This work investigates the use of the depth sensor of HoloLens 2 for registration in surgical navigation.
Methods: An AR depth-based registration framework was developed.
Sci Rep
March 2025
School of Electronics Information Engineering, Xi'an Technological University, Xi'an, 710021, China.
This study presents PillarFocusNet, a novel network about 3D point cloud object detection that optimizes the PointPillars framework to improve detection performance. First, we propose the Pillar Clustering Sampling Method to address the sparse and uneven distribution of 3D point cloud data. Second, we introduce the Mixed Pooling Dilated Convolution Layer (MPDC layer) to enhance feature extraction.
View Article and Find Full Text PDFSci Data
March 2025
Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
4D radar has higher point cloud density and precise vertical resolution than conventional 3D radar, making it promising for adverse scenarios in the environmental perception of autonomous driving. However, 4D radar is more noisy than LiDAR and requires different filtering strategies that affect the point cloud density and noise level. Comparative analyses of different point cloud densities and noise levels are still lacking, mainly because the available datasets use only one type of 4D radar, making it difficult to compare different 4D radars in the same scenario.
View Article and Find Full Text PDFFront Neurosci
February 2025
Centre for Brain Research, Indian Institute of Science (IISc), Bengaluru, Karnataka, India.
Introduction: Mild cognitive impairment (MCI), often linked to early neurodegeneration, is associated with subtle disruptions in brain connectivity. In this paper, the applicability of persistent homology, a cutting-edge topological data analysis technique is explored for classifying MCI subtypes.
Method: The study examines brain network topology derived from fMRI time series data.
IEEE Trans Vis Comput Graph
March 2025
This paper presents a Task-Free eye-tracking dataset for Dynamic Point Clouds (TF-DPC) aimed at investigating visual attention. The dataset is composed of eye gaze and head movements collected from 24 participants observing 19 scanned dynamic point clouds in a Virtual Reality (VR) environment with 6 degrees of freedom. We compare the visual saliency maps generated from this dataset with those from a prior task-dependent experiment (focused on quality assessment) to explore how high-level tasks influence human visual attention.
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