3D Reconstruction Of Computed Tomography Images Research Articles

Quantitative analysis of pore characteristics of nanocellulose reinforced cementitious tailings fills using 3D reconstruction of CT images

This study aims at analyzing the influence of contents and types of various nanocelluloses (e.g., CNF, CNC, and MFC) and intermediate microstructure on strength/fracture features of cementitious tailings backfill (CTB). This is important in understanding the environmental implications of tailings and crushed rock accumulation. Researchers explored the strength behavior of nanocellulose-reinforced CTB (NRCTB) while analyzing quantitatively their spatial structure/fractures through SEM and CT (computed tomography) methods. Results highlight that optimizing the content of nanocelluloses can boost the pore structure of NRCTB. CTB reinforced with CNF and CNC exhibit specific pore structures, while MFC-CTBs shows a different pattern. The addition of nanocellulose helps in suppressing cracking. The overall porosity of the different CTB samples varied. The study also proposes a dual nanocellulose-pore network model to explain the microscopic enhancement mechanism. The findings subsidize the understanding of NRCTB's microscopic enhancement mechanisms and can have implications for mitigating environmental damage caused by tailings-crushed rock accumulation.

Influence of Lingual Tonsillar Volume in Patients with Obstructive Sleep Apnea.

This study aimed to evaluate the influence of lingual tonsil (LT) volume measured using a three-dimensional (3D) reconstruction volume rendering program on clinical parameters and polysomnography (PSG) results. A total of 100 patients who underwent PSG, computed tomography (CT), and allergy test from April 2016 to April 2020 were randomly selected. LT volume was measured using an imaging software program that enables 3D reconstruction of CT images. PSG parameters were analyzed by dividing the subjects into two groups according to LT volume (each 50 people). Based on the medial volume of 0.863 cm3, the upper half LT volume group and the lower half LT volume group were analyzed. Clinical factors such as body weight, neck circumference, body mass index (BMI), and age showed no difference between the two groups. Among PSG parameters, supine arousal index and non-rapid eye movement (NREM) arousal index were significantly higher in the upper half LT volume group (p = 0.012, 0.037). However, there was no significant difference in apnea-hypopnea index (AHI) between the upper and lower half LT volume groups (p = 0.749). Arousal snoring index and REM arousal index also showed no difference between the two groups. The prevalence of allergic rhinitis was not different in the two groups. High LT volume is associated with NREM arousal and arousal in the supine position, but it is not related to AHI.

Semi-homogeneous model of coal based on 3D reconstruction of CT images and its seepage-deformation characteristics

To study the effect of isolated pores on gas seepage and coal deformation, computed tomography (CT) scanning was used to analyse the porosity and fractal characteristics of isolated pores. A geometric model of coal was then established using 3D reconstruction. Finally, a seepage-stress semi-homogeneous coupling model was established by considering the adsorption and desorption of gas. The significant difference between this model and the existing models is that the non-homogeneity of isolated pores is considered. The results show that the porosity of the isolated pores is 5.73%, accounting for 58.41% of the total pores, and the diameter is concentrated in the range of 0–10 μm. The average fractal dimension of the connected pores (1.25) is smaller than that of the isolated pores (1.35), indicating that isolated pores have a more complex structure. The gas seepage velocity is negatively correlated with the isolated pore porosity, and it varies strongly at each point of the model, with a maximum and minimum of 5.08 m/s and 1.45 × 10−4 m/s, respectively. The inhomogeneous distribution of isolated pores led to a differential deformation of the model. The total displacement of the slices varies from 13,550 μm to 14,300 μm and decreases with increasing isolated pore porosity and fractal dimension. Both low fractal dimension and low isolated pore porosity increase the deformation.

Effect of High-Flow Nasal Cannula for Hypoxemia Following Sun's Procedure in Acute Aortic Dissection Type a Patients.

Background: Patients with acute aortic dissection type A (AADA) often have hypoxemia (partial pressure of oxygen [PaO2]/fraction of inspired oxygen [FiO2] <300 mmHg) before weaning in the intensive care unit (ICU). This study compared the efficacy of high-flow nasal cannula (HFNC) with that of conventional oxygen therapy (COT) in patients with AADA following Sun's procedure.Methods: The medical records of 87 adult patients with AADA who underwent Sun's procedure and met the inclusion criteria (PaO2/FiO2 <300 mmHg before weaning) were retrospectively analyzed. After surgery, 41 patients were treated with HFNC and 46 were treated with COT. The oxygenation level, FiO2, partial pressure of carbon dioxide, heart rate, respiratory rate, subjective discomfort, and reintubation rate were recorded. The difference in lung volume loss between the HFNC and COT groups was assessed using the radiological atelectasis score (chest radiograph) or calculated from three-dimensional (3D) reconstructed computed tomography (CT) images.Results: From day 1 to day 5 after weaning, there was no significant difference in PaO2/FiO2 between the HFNC and COT groups, although the FiO2 was significantly lower in the HFNC group than in the COT group (P < 0.05). Further studies indicated that the percentage of lung volume loss (pleural effusion and/or pulmonary atelectasis) by 3D reconstruction of CT images at 4–8 days post-operation was significantly lower in the HFNC group (P < 0.05). The subjective experience of breathing discomfort, reintubation rate, and length of stay in the ICU were significantly reduced in the HFNC group (P < 0.05). There was no significant difference in readmission to the ICU and in-hospital mortality between the two groups.Conclusions: HFNC can be used as an effective oxygen therapy for AADA patients with hypoxemia after Sun's procedure.

Study on seepage and deformation characteristics of coal microstructure by 3D reconstruction of CT images at high temperatures

To study the seepage and deformation characteristics of coal at high temperatures, coal samples from six different regions were selected and subjected to computed tomography (CT) scanning studies. In conjunction with ANSYS software, 3D reconstruction of CT images was used for the establishment of fluid-solid conjugate heat transfer model and coal thermal deformation model based on the microstructures of coal. In addition, the structure of coal was studied in 2D and 3D perspectives, followed by the analysis of seepage and deformation characteristics of coal at high temperatures. The results of this study indicated that porosity positively correlated with the fractal dimension, and the connectivity and seepage performances were roughly identical from 2D and 3D perspectives. As the porosity increased, the fractal dimension of coal samples became larger and the pore-fracture structures became more complex. As a result, the permeability of coal samples decreased. In the meantime, fluid was fully heated, generating high-temperature water at outlet. However, when the porosity was low, the outlet temperature was very high. The average deformation of coal skeleton with different pore-fracture structures at high temperatures showed a trend of initial increase and subsequent decrease with the increase of porosity and fractal dimension. The maximum deformation of coal skeleton positively correlated with connectivity but negatively correlated with the fractal dimension.

Patient Counseling Through the Pelvicalyceal-shaped Labyrinth: In Search of an Easy Understanding of the Upcoming Stone Removal: A Pilot Study

ObjectiveTo investigate the impact of a mobile application (app) displaying a visualization of the internal anatomy of the pelvicalyceal systemPCS and of kidney stones on patient understanding of their affected kidney anatomy and their upcoming percutaneous nephrolithotripsy (PCNL). Materials and methodsOne-hundred patients who required PCNL were included in this study, and all patients were nonrandomly distributed into 2 groups: counseled using only 3D-reconstructed computed tomography (CT) images (group 1) or using only the “InsKid” app (group 2). Patient data were obtained from CT scans as Digital Imaging and Communications in Medicine format and converted into stereolithography (STL) format. All patients completed the questionnaire after counseling, and the results were compared between groups. ResultsPatients from group 2 better understood the anatomy of their affected kidney by 53%; awareness regarding their stone location was better by 32%; the steps of planned surgery, as well as possible complications, were more transparent for patients using the app by 24% and 56%, respectively. The number of patients who were dissatisfied with the mobile counseling dropped by 70%. The average duration of consultation with the 3D reconstruction of CT images was 10.9 ± 0.6 min, while counseling using our program reliably led to a reduction in this duration (7.3 ± 0.5 min). ConclusionThe InsKid app is a freely available, easy-to-use educational software that improves patient counseling without considerable financial expense or long waiting periods for use.

Deep Encoder-Decoder Adversarial Reconstruction(DEAR) Network for 3D CT from Few-View Data.

X-ray computed tomography (CT) is widely used in clinical practice. The involved ionizing X-ray radiation, however, could increase cancer risk. Hence, the reduction of the radiation dose has been an important topic in recent years. Few-view CT image reconstruction is one of the main ways to minimize radiation dose and potentially allow a stationary CT architecture. In this paper, we propose a deep encoder-decoder adversarial reconstruction (DEAR) network for 3D CT image reconstruction from few-view data. Since the artifacts caused by few-view reconstruction appear in 3D instead of 2D geometry, a 3D deep network has a great potential for improving the image quality in a data driven fashion. More specifically, our proposed DEAR-3D network aims at reconstructing 3D volume directly from clinical 3D spiral cone-beam image data. DEAR is validated on a publicly available abdominal CT dataset prepared and authorized by Mayo Clinic. Compared with other 2D deep learning methods, the proposed DEAR-3D network can utilize 3D information to produce promising reconstruction results.

Efficient and robust 3D CT image reconstruction based on total generalized variation regularization using the alternating direction method

Iterative reconstruction algorithms for computed tomography (CT) through total variation regularization based on piecewise constant assumption can produce accurate, robust, and stable results. Nonetheless, this approach is often subject to staircase artefacts and the loss of fine details. To overcome these shortcomings, we introduce a family of novel image regularization penalties called total generalized variation (TGV) for the effective production of high-quality images from incomplete or noisy projection data for 3D reconstruction. We propose a new, fast alternating direction minimization algorithm to solve CT image reconstruction problems through TGV regularization. Based on the theory of sparse-view image reconstruction and the framework of augmented Lagrange function method, the TGV regularization term has been introduced in the computed tomography and is transformed into three independent variables of the optimization problem by introducing auxiliary variables. This new algorithm applies a local linearization and proximity technique to make the FFT-based calculation of the analytical solutions in the frequency domain feasible, thereby significantly reducing the complexity of the algorithm. Experiments with various 3D datasets corresponding to incomplete projection data demonstrate the advantage of our proposed algorithm in terms of preserving fine details and overcoming the staircase effect. The computation cost also suggests that the proposed algorithm is applicable to and is effective for CBCT imaging. Theoretical and technical optimization should be investigated carefully in terms of both computation efficiency and high resolution of this algorithm in application-oriented research.

Noise Analysis in Computed Tomography (CT) Image Reconstruction using QR-Decomposition Algorithm

In this paper, the noise of 3D computed tomography (CT) image reconstruction using QR-Decomposition is analyzed. There are several types of image noise that can interfere with the interpretation of an image. Here, the noise introduced by the reconstruction process is studied. In this analysis, condition numbers are calculated with different CT model parameters, three dimensional (3D) CT image reconstruction with simulated and real data are performed, image noise analysis is performed through various image quality parameters and the condition number of the linear system is related with the image quality parameters. Results show the condition number's dependence on the CT model. Image reconstructions with simulated data show errors significantly below the condition number theoretical bound and image reconstructions with real data show that quality improvements depend strongly on the condition number. This allows a reduction on the number of projections without compromising image quality and places this reconstruction method as a strong candidate for low-dose 3D CT imaging reconstruction.

WE‐G‐BRC‐02: A Portable Optical CT Scanner for Interactive Teaching of Imaging Principles

Purpose: To develop a portable scanner that demonstrates the principles of radiography and computed tomography (CT). Methods: The traditional methods for teaching the physics of medical imaging rely on lectures, followed by demonstrations on a clinical system that is not easily accessible or programmed for educational purposes. We have developed a scaled‐down portable CT imaging system suitable for interactive “real time” demonstrations using a laptop computer during a classroom or lab session. Our optical system uses light rays in lieu of x‐rays so that experiments can be conducted while posing no electrical or radiation hazards to instructors and students. The desk‐top CT imaging device will be supplied with a learning kit of experimental test phantoms, lab manuals, instructional videos, and specialized software that demonstrate 2D radiographic and 3D CT image reconstruction methods. These approaches are relevant to imaging systems used in digital diagnostic imaging and image‐guided therapy. Results: A low‐cost portable system (&lt; $15,000) has been manufactured (http://www.deskcat.com/) to enrich the studentˈs learning experience and improve the retention of fundamental imaging concepts. Students learn about spatial resolution, contrast resolution, system linearity, image artifacts and they perform quantitative measurements in 3D space, using image visualization software tools and specialized test phantoms (7.2 cm diameter × 5.3 cm long). Early reaction from instructors and students alike has been very encouraging. Conclusions: This learning package should prove attractive to universities with medical physics programs in Departments of Physics, Medical Biophysics, or Biomedical Engineering, as well as Medical Schools with residency training programs (Medical Imaging, Radiation Oncology). The systemˈs modular nature allows extensions for future coverage of related topics such as nuclear and molecular SPECT imaging. Through future developments, it may also be possible to model the dose deposition patterns from intensity‐modulated radiotherapy beams using ultraviolet exposure of radiochromic gel volumes.This research was sponsored by the Ministry of Research and Innovation, Government of Ontario, Canada (ORDCF Grant, OCITS Project) and by Modus Medical Devices as the industry partner. We also thank The University of Western Ontario for providing funding through its “Fellowship for Teaching Innovation”. This supported one of the authors (RT) during a summer studentship.

A parallel implementation of 3D CT image reconstruction on the Cell Broadband Engine

AbstractCone‐beam X‐ray computed tomography (CT) is attracting increasing attention due to its applications in medicine, biomedical sciences, material engineering, and non‐destructive industrial evaluation. Rapid volumetric image reconstruction is highly desirable in all these fields for prompt visualization and analysis of complex structures of interest. However, in most applications, volumetric image reconstruction is still a very demanding computational task. The Cell Broadband Engine architecture (CBEA) is a novel microprocessor architecture designed to provide power‐efficient and cost‐effective high‐performance processing for some of the world's most demanding applications, including next generation game consoles. Applications that show special promise of benefiting from CBEA are medical imaging, security and surveillance, digital media, entertainment, communications, and certain scientific workloads. We believe that the CBEA is a good vehicle for processing 3D CT image reconstructions because it has the capability of reaching 200 Gfps. We implemented 3D CT image reconstruction on the CBEA. However, the programming scheme of the CBEA is different from single‐core architectures. To archive peak performance on the CBEA, coding optimizations are needed to exploit the unique features of the hardware. In this paper, we describe the parallelization of the 3D image reconstruction algorithm on the CBEA. The results show that the CBEA can achieve significant run time savings. Copyright © 2009 John Wiley &amp; Sons, Ltd.