246 research outputs found
Local ROI Reconstruction via Generalized FBP and BPF Algorithms along More Flexible Curves
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
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
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- 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
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
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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