In the original article, there was a mistake in the content of Table 2 page 8 column 1 as published. The values of the mean and standard deviation of the virtual-to-real overlay error in visual angles, which are reported for different checkerboard distances, are to be corrected. Due to a typing error within the data analysis code, we mistakenly considered an erroneous value of the average angular resolution for the eye-replacement camera. This scale factor is used to pass from the original registration errors (expressed in pixel) to the angular registration errors (in arcmin). The value of the average angular resolution is $\approx 2.67$≈2.67 arcmin/pixel. The corrected Table 2 appears below.
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http://dx.doi.org/10.1109/TVCG.2022.3176417 | DOI Listing |
Phys Med Biol
January 2025
National Institute of Radiological Sciences, 4-9-1 Anagawa, Inage-ku, Chiba, 263-8555, JAPAN.
PET has become an important clinical modality but is limited to imaging positron emitters. Recently, PET imaging withZr, which has a half-life of 3 days, has attracted much attention in immuno-PET to visualize immune cells and cancer cells by targeting specific antibodies on the cell surface. However,Zr emits a single gamma ray at 909 keV four times more frequently than positrons, causing image quality degradation in conventional PET.
View Article and Find Full Text PDFSci Rep
January 2025
School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Anatomical Landmark detection in CT-Scan images is widely used in the identification of skeletal disorders. However, the traditional process of manually detecting anatomical landmarks, especially in three dimensions, is both time-consuming and prone to human errors. We propose a novel, deep-learning-based approach to automatic detection of 3D landmarks in CT images of the lower limb.
View Article and Find Full Text PDFAdv Sci (Weinh)
December 2024
Department of Information Communication, Army Academy of Armored Forces, Beijing, 100072, China.
Generating computer-generated holograms (CGHs) for 3D scenes by learning-based methods can reconstruct arbitrary 3D scenes with higher quality and faster speed. However, the homogenization and difficulty of obtaining 3D high-resolution datasets seriously limit the generalization ability of the model. A novel approach is proposed to train 3D encoding models based on convolutional neural networks (CNNs) using 2D image datasets.
View Article and Find Full Text PDFEur J Orthop Surg Traumatol
December 2024
Department of Orthopedics and Trauma, Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, Brazil.
Purpose: Although several techniques have been described for bent intramedullary nail removal, there is no universally accepted strategy. We hypothesized that a device based on the action principle of a three-point bend fixture could facilitate extraction of bent intramedullary nails; this paper describes its design and experimental testing.
Methods: Five large synthetic left femurs and five steel intramedullary nails were used.
J Bone Miner Res
December 2024
Division of Endocrinology/Metabolic Bone Disease Service, Hospital for Special Surgery, New York, NY.
Opportunistic screening is essential to improve the identification of individuals with osteoporosis. Our group has utilized image texture features to assess bone quality using clinical MRIs. We have previously demonstrated that greater heterogeneity of MRI texture related to history of fragility fractures, lower bone density, and worse microarchitecture.
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