216 research outputs found

    Case Report: Pulmonary Typical Carcinoid with Multi-organ Metastasis

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    Local ROI Reconstruction via Generalized FBP and BPF Algorithms along More Flexible Curves

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    We study the local region-of-interest (ROI) reconstruction problem, also referred to as the local CT problem. Our scheme includes two steps: (a) the local truncated normal-dose projections are extended to global dataset by combining a few global low-dose projections; (b) the ROI are reconstructed by either the generalized filtered backprojection (FBP) or backprojection-filtration (BPF) algorithms. The simulation results show that both the FBP and BPF algorithms can reconstruct satisfactory results with image quality in the ROI comparable to that of the corresponding global CT reconstruction

    New advances in catalysts for C9 petroleum resin hydrogenation

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    C9 petroleum resin is a thermoplastic polymer produced by polymerization of C9 fraction obtaining from the steam cracking unit, and could be catalytic hydrogenated to remove the ethylenic C=C bond, aromatic ring with improved physical properties. The research progress in the efficiency supported nickel or/and palladium catalysts for C9 petroleum resin hydrogenation was illustrated and reviewed, further development was discussed

    Omni-Line-of-Sight Imaging for Holistic Shape Reconstruction

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    We introduce Omni-LOS, a neural computational imaging method for conducting holistic shape reconstruction (HSR) of complex objects utilizing a Single-Photon Avalanche Diode (SPAD)-based time-of-flight sensor. As illustrated in Fig. 1, our method enables new capabilities to reconstruct near-360360^\circ surrounding geometry of an object from a single scan spot. In such a scenario, traditional line-of-sight (LOS) imaging methods only see the front part of the object and typically fail to recover the occluded back regions. Inspired by recent advances of non-line-of-sight (NLOS) imaging techniques which have demonstrated great power to reconstruct occluded objects, Omni-LOS marries LOS and NLOS together, leveraging their complementary advantages to jointly recover the holistic shape of the object from a single scan position. The core of our method is to put the object nearby diffuse walls and augment the LOS scan in the front view with the NLOS scans from the surrounding walls, which serve as virtual ``mirrors'' to trap lights toward the object. Instead of separately recovering the LOS and NLOS signals, we adopt an implicit neural network to represent the object, analogous to NeRF and NeTF. While transients are measured along straight rays in LOS but over the spherical wavefronts in NLOS, we derive differentiable ray propagation models to simultaneously model both types of transient measurements so that the NLOS reconstruction also takes into account the direct LOS measurements and vice versa. We further develop a proof-of-concept Omni-LOS hardware prototype for real-world validation. Comprehensive experiments on various wall settings demonstrate that Omni-LOS successfully resolves shape ambiguities caused by occlusions, achieves high-fidelity 3D scan quality, and manages to recover objects of various scales and complexity

    Poor-prognosis disclosure preference in cancer patient-caregiver dyads and its association with their quality of life and perceived stress: a cross-sectional survey in mainland China

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    Background This study attempted to examine the discordance between family caregivers and cancer patients in their poor-prognosis disclosure preferences in mainland China and then ascertained the associations between quality of life (QoL), perceived stress, and poor-prognosis disclosure preferences. Methods Six hundred fifty-one pairs of inpatients and their matched caregivers (participation rate = 92.2%) were recruited in this cross-sectional survey. A set of paired self-administered questionnaires were completed independently by patient–caregiver dyads. Results Fewer family caregivers than cancer patients felt that poor prognosis should be disclosed to patients (61.2% vs. 90.0%, p < 0.001). Patients' positive poor-prognosis disclosure preference was associated with patients' better QoL (p < 0.05) and caregivers' reduced perceived stress levels (p = 0.013). However, caregivers' poor-prognosis disclosure preference correlated only with their own physical state (p = 0.028). Moreover, the caregivers who concurred with patients in positive poor-prognosis disclosure preference were more likely to experience a better QoL (p < 0.05) and lower perceived stress levels (p = 0.048) in the III–IV stage subgroup. Conclusions There was a significant discrepancy in poor-prognosis disclosure preference between cancer patients and caregivers in China. The caregivers' preference of concealing poor prognosis from patients was not related to cancer patients' QoL or perceived stress. In addition, caregivers had better QoL and lower stress levels when they held the same positive poor-prognosis disclosure preference as the patients

    Metal artifact reduction in dental CT images using polar mathematical morphology

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    Most dental implant planning systems use a 3D representation of the CT scan of the patient under study as it provides a more intuitive view of the human jaw. The presence of metallic objects in human jaws, such as amalgam or gold fillings, provokes several artifacts like streaking and beam hardening which makes the reconstruction process difficult. In order to reduce these artifacts, several methods have been proposed using the raw data, directly obtained from the tomographs, in different ways. However, in DICOM-based applications this information is not available, and thus the need of a new method that handles this task in the DICOM domain. The presented method performs a morphological filtering in the polar domain yielding output images less affected by artifacts (even in cases of multiple metallic objects) without causing significant smoothing of the anatomic structures, which allows a great improvement in the 3D reconstruction. The algorithm has been automated and compared to other image denoising methods with successful results. (C) 2010 Elsevier Ireland Ltd. All rights reserved.This work has been supported by the project MIRACLE (DPI2007-66782-C03-01-AR07) of Spanish Ministerio de Educacion y Ciencia.Naranjo Ornedo, V.; Llorens Rodríguez, R.; Alcañiz Raya, ML.; López-Mir, F. (2011). Metal artifact reduction in dental CT images using polar mathematical morphology. Computer Methods and Programs in Biomedicine. 102(1):64-74. https://doi.org/10.1016/j.cmpb.2010.11.009S6474102
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