A Practical Statistical Approach to the Reconstruction Problem Using a Single Slice Rebinning Method

AbstractThe paper presented here describes a new practical approach to the reconstruction problem applied to 3D spiral x-ray tomography. The concept we propose is based on a continuous-to-continuous data model, and the reconstruction problem is formulated as a shift invariant system. This original reconstruction method is formulated taking into consideration the statistical properties of signals obtained by the 3D geometry of a CT scanner. It belongs to the class of nutating reconstruction methods and is based on the advanced single slice rebinning (ASSR) methodology. The concept shown here significantly improves the quality of the images obtained after reconstruction and decreases the complexity of the reconstruction problem in comparison with other approaches. Computer simulations have been performed, which prove that the reconstruction algorithm described here does indeed significantly outperforms conventional analytical methods in the quality of the images obtained.

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Novel Reconstruction Using Roux-en-Y Plus Antral Obstruction Following Proximal Gastrectomy: Feasibility and Quality of Life Benefits

10.21203/rs.2.11422/v1 ◽

2019 ◽

Author(s):

Dejun Yang ◽

Changming Wang ◽

Hongbing Fu ◽

Ziran Wei ◽

Xin Zhang ◽

...

Keyword(s):

Quality Of Life ◽

Reflux Esophagitis ◽

Proximal Gastrectomy ◽

Partial Gastrectomy ◽

Incidence Rates ◽

Reconstruction Method ◽

Reflux Symptoms ◽

Reconstruction Methods ◽

Postoperative Reflux

Abstract Background and Aims Routine gastroesophagostomy has been shown to have adverse effects on the recovery of digestive functions and quality of life because patients typically experience reflux symptoms after proximal gastrectomy. This study was performed to assess the feasibility and quality of life benefits of a novel reconstruction method termed Roux-en-Y anastomosis plus antral obstruction (RYAO) following proximal partial gastrectomy. Methods A total of 73 patients who underwent proximal gastrectomy from June 2015 to June 2017 were divided into two groups according to digestive reconstruction methods [RYAO (37 patients) and conventional esophagogastric anastomosis with pyloroplasty (EGPP, 36 patients)]. Clinical data were compared between the two groups retrospectively. Results The mean operative time for digestive reconstruction was slightly longer in the RYAO group than in the EGPP group. However, the incidence of postoperative short-term complications did not differ between the RYAO and the EGPP groups. At the 6-month follow-up, the incidence rates of both reflux esophagitis and gastritis were lower in the RYAO group than in the EGPP group (P = 0.002). Additionally, body weight recovery was better in the RYAO group (P = 0.028). The scale tests indicated that compared with the patients in the EGPP group, the patients in the RYAO group had significantly reduced reflux, nausea and vomiting and reported improvements in their overall health status and quality of life (all P < 0.05). Conclusion RYAO reconstruction may be a feasible procedure to reduce postoperative reflux symptoms and the incidence of reflux esophagitis and gastritis, thus improving patient quality of life after proximal gastrectomy.

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Improving Non-Cartesian MRI Reconstruction through Discontinuity Subtraction

International Journal of Biomedical Imaging ◽

10.1155/ijbi/2006/87092 ◽

2006 ◽

Vol 2006 ◽

pp. 1-9 ◽

Cited By ~ 3

Author(s):

Jiayu Song ◽

Qing Huo Liu

Keyword(s):

Reconstruction Method ◽

Reconstruction Methods ◽

Spread Function ◽

Data Fidelity ◽

Mri Reconstruction ◽

Magnetic Resonance Imaging Mri ◽

Space Data ◽

2D And 3D ◽

Undersampled Data

Non-Cartesian sampling is widely used for fast magnetic resonance imaging (MRI). Accurate and fast image reconstruction from non-Cartesiank-space data becomes a challenge and gains a lot of attention. Images provided by conventional direct reconstruction methods usually bear ringing, streaking, and other leakage artifacts caused by discontinuous structures. In this paper, we tackle these problems by analyzing the principal point spread function (PSF) of non-Cartesian reconstruction and propose a leakage reduction reconstruction scheme based on discontinuity subtraction. Data fidelity ink-space is enforced during each iteration. Multidimensional nonuniform fast Fourier transform (NUFFT) algorithms are utilized to simulate thek-space samples as well as to reconstruct images. The proposed method is compared to the direct reconstruction method on computer-simulated phantoms and physical scans. Non-Cartesian sampling trajectories including 2D spiral, 2D and 3D radial trajectories are studied. The proposed method is found useful on reducing artifacts due to high image discontinuities. It also improves the quality of images reconstructed from undersampled data.

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Evaluation of the Feasibility and Quantitative Accuracy of a Generalized Scatter 2D PET Reconstruction Method

ISRN Biomedical Imaging ◽

10.1155/2013/943051 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 9

Author(s):

Hongyan Sun ◽

Stephen Pistorius

Keyword(s):

Expectation Maximization ◽

Reconstruction Algorithm ◽

Reconstruction Method ◽

Diagnostic Quality ◽

Reconstruction Methods ◽

Positron Emission ◽

Quantitative Accuracy ◽

Maximum Likelihood Expectation Maximization ◽

Pet Reconstruction ◽

Limiting Case

Scatter degrades the contrast and quantitative accuracy of positron emission tomography (PET) images, and most methods for estimating and correcting scattered coincidences in PET subtract scattered events from the measured data. Compton scattering kinematics can be used to map out the locus of possible scattering locations. These curved lines (2D) or surfaces (3D), which connect the coincidence detectors, encompass the surface (2D) or volume (3D) where the decay occurs. In the limiting case where the scattering angle approaches zero, the scattered coincidence approaches the true coincidence. Therefore, both true and scattered coincidences can be considered similarly in a generalized scatter maximum-likelihood expectation-maximization reconstruction algorithm. The proposed method was tested using list-mode data obtained from a GATE simulation of a Jaszczak-type phantom. For scatter fractions from 10% to 60%, this approach reduces noise and improves the contrast recovery coefficients by 0.5–3.0% compared with reconstructions using true coincidences and by 3.0–24.5% with conventional reconstruction methods. The results demonstrate that this algorithm is capable of producing images entirely from scattered photons, eliminates the need for scatter corrections, increases image contrast, and reduces noise. This could be used to improve diagnostic quality and/or to reduce patient dose and radiopharmaceutical cost.

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A New Statistical Reconstruction Method for the Computed Tomography Using an X-Ray Tube with Flying Focal Spot

Journal of Artificial Intelligence and Soft Computing Research ◽

10.2478/jaiscr-2021-0016 ◽

2021 ◽

Vol 11 (4) ◽

pp. 271-286

Author(s):

Robert Cierniak ◽

Piotr Pluta ◽

Marek Waligóra ◽

Zdzisław Szymański ◽

Konrad Grzanek ◽

...

Keyword(s):

Computed Tomography ◽

Focal Spot ◽

Reconstruction Method ◽

Reconstruction Procedure ◽

X Ray ◽

Statistical Reconstruction ◽

Reconstruction Methods ◽

Ct Scanners ◽

The Impact

Abstract This paper presents a new image reconstruction method for spiral cone- beam tomography scanners in which an X-ray tube with a flying focal spot is used. The method is based on principles related to the statistical model-based iterative reconstruction (MBIR) methodology. The proposed approach is a continuous-to-continuous data model approach, and the forward model is formulated as a shift-invariant system. This allows for avoiding a nutating reconstruction-based approach, e.g. the advanced single slice rebinning methodology (ASSR) that is usually applied in computed tomography (CT) scanners with X-ray tubes with a flying focal spot. In turn, the proposed approach allows for significantly accelerating the reconstruction processing and, generally, for greatly simplifying the entire reconstruction procedure. Additionally, it improves the quality of the reconstructed images in comparison to the traditional algorithms, as confirmed by extensive simulations. It is worth noting that the main purpose of introducing statistical reconstruction methods to medical CT scanners is the reduction of the impact of measurement noise on the quality of tomography images and, consequently, the dose reduction of X-ray radiation absorbed by a patient. A series of computer simulations followed by doctor’s assessments have been performed, which indicate how great a reduction of the absorbed dose can be achieved using the reconstruction approach presented here.

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Reconstruction of High-Resolution Computed Tomography Image in Sinogram Space

International Journal of Mathematics and Computers in Simulation ◽

10.46300/9102.2021.15.15 ◽

2021 ◽

Vol 15 ◽

pp. 84-88

Author(s):

Osama A. Omer

Keyword(s):

Computed Tomography ◽

High Resolution ◽

Image Quality ◽

Computational Cost ◽

Super Resolution ◽

Reconstruction Method ◽

High Resolution Computed Tomography ◽

Resolution Image ◽

Reconstruction Methods

An important part of any computed tomography (CT) system is the reconstruction method, which transforms the measured data into images. Reconstruction methods for CT can be either analytical or iterative. The analytical methods can be exact, by exact projector inversion, or non-exact based on Back projection (BP). The BP methods are attractive because of thier simplicity and low computational cost. But they produce suboptimal images with respect to artifacts, resolution, and noise. This paper deals with improve of the image quality of BP by using super-resolution technique. Super-resolution can be beneficial in improving the image quality of many medical imaging systems without the need for significant hardware alternation. In this paper, we propose to reconstruct a high-resolution image from the measured signals in Sinogram space instead of reconstructing low-resolution images and then post-process these images to get higher resolution image.

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A Dense Deformable Model for Craniofacial Reconstruction

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.108.282 ◽

2011 ◽

Vol 108 ◽

pp. 282-288

Author(s):

Yong Li Hu ◽

Yan Feng Sun ◽

Bao Cai Yin ◽

Ming Quan Zhou

Keyword(s):

Deformable Model ◽

Reconstruction Method ◽

Model Matching ◽

Ct Scanner ◽

Craniofacial Reconstruction ◽

Face Shape ◽

Reconstruction Methods ◽

Soft Tissue Thickness ◽

The Face ◽

Point To Point

The traditional craniofacial reconstruction methods construct the face shape according to the soft tissue thickness measured at a sparse set of landmarks on the skull. But the landmarks are difficult to detect and generally need human interactive assistance. The quantity and position of the landmarks lack for uniform definition. We propose an automatic craniofacial reconstruction method based on a dense deformable model. To construct the model, hundreds of skull and face samples are acquired by CT scanner. A dense mesh registration algorithm is proposed to build the point-to-point correspondences of the samples. Based on the aligned samples, the deformable model is constructed. For a given skull, the reconstructed face is obtained by a model matching procedure. Experimental results indicate that the deformable model has good performance for craniofacial reconstruction.

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Improving the Accuracy of Automatic Reconstruction of 3D Complex Buildings Models from Airborne Lidar Point Clouds

Remote Sensing ◽

10.3390/rs12101643 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1643 ◽

Cited By ~ 1

Author(s):

Marek Kulawiak ◽

Zbigniew Lubniewski

Keyword(s):

Surface Reconstruction ◽

Spatial Data ◽

Measurement Data ◽

Point Clouds ◽

3D Models ◽

Airborne Lidar ◽

Reconstruction Method ◽

Cloud Data ◽

Reconstruction Methods

Due to high requirements of variety of 3D spatial data applications with respect to data amount and quality, automatized, efficient and reliable data acquisition and preprocessing methods are needed. The use of photogrammetry techniques—as well as the light detection and ranging (LiDAR) automatic scanners—are among attractive solutions. However, measurement data are in the form of unorganized point clouds, usually requiring transformation to higher order 3D models based on polygons or polyhedral surfaces, which is not a trivial process. The study presents a newly developed algorithm for correcting 3D point cloud data from airborne LiDAR surveys of regular 3D buildings. The proposed approach assumes the application of a sequence of operations resulting in 3D rasterization, i.e., creation and processing of a 3D regular grid representation of an object, prior to applying a regular Poisson surface reconstruction method. In order to verify the accuracy and quality of reconstructed objects for quantitative comparison with the obtained 3D models, high-quality ground truth models were used in the form of the meshes constructed from photogrammetric measurements and manually made using buildings architectural plans. The presented results show that applying the proposed algorithm positively influences the quality of the results and can be used in combination with existing surface reconstruction methods in order to generate more detailed 3D models from LiDAR scanning.

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Three-Dimensional Reconstruction Method for Machined Surface Topography Based on Gray Gradient Constraints

Applied Sciences ◽

10.3390/app9030591 ◽

2019 ◽

Vol 9 (3) ◽

pp. 591

Author(s):

Wei-Chao Shi ◽

Jian-Ming Zheng ◽

Yan Li ◽

Xu-Bo Li

Keyword(s):

Surface Topography ◽

Three Dimensional ◽

Surface Characteristics ◽

Reconstruction Algorithm ◽

Shape From Shading ◽

Reconstruction Method ◽

Machined Surface ◽

Reconstruction Methods ◽

Product Function ◽

Dimensional Reconstruction

In the modern engineering field, recovering the machined surface topography is important for studying mechanical product function and surface characteristics by using the shape from shading (SFS)-based reconstruction method. However, due to the limitations of many constraints and oversmoothing, the existing SFS-based reconstruction methods are not suitable for machined surface topography. This paper presents a new three-dimensional (3D) reconstruction method of machined surface topography. By combining the basic principle of SFS and the analytic method, the analytic model of a surface gradient is established using the gray gradient as a constraint condition. By efficiently solving the effect of quantization errors and ambiguity of the gray scale on reconstruction accuracy using a wavelet denoising algorithm and image processing technology, the reconstruction algorithm is implemented for machined surface topography. Experimental results on synthetic images and machined surface topography images show that the proposed algorithm can accurately and efficiently recover the 3D shape of machined surface topography.

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Various Kinds of Functional Digestive Tract Reconstruction Methods After Proximal Gastrectomy

Frontiers in Oncology ◽

10.3389/fonc.2021.685717 ◽

2021 ◽

Vol 11 ◽

Author(s):

Shuaibing Lu ◽

Fei Ma ◽

Zhandong Zhang ◽

Liangqun Peng ◽

Wei Yang ◽

...

Keyword(s):

Quality Of Life ◽

Gastric Cancer ◽

Total Gastrectomy ◽

Digestive Tract ◽

Proximal Gastrectomy ◽

Perioperative Outcomes ◽

Reconstruction Method ◽

Proximal Gastric Cancer ◽

Reconstruction Methods

The incidence of proximal gastric cancer has shown a rising trend in recent years. Surgery is still the main way to cure proximal gastric cancer. Total gastrectomy with D2 lymph node dissection was considered to be the standard procedure for proximal gastric cancer in the past several decades. However, in recent years, many studies have confirmed that proximal gastrectomy can preserve part of the stomach function and can result in a better quality of life of the patient than total gastrectomy. Therefore, proximal gastrectomy is increasingly used in patients with proximal gastric cancer. Unfortunately, there are some concerns after proximal gastrectomy with traditional esophagogastrostomy. For example, the incidence of reflux esophagitis in patients who underwent proximal gastrectomy with traditional esophagogastrostomy is significantly higher than those patients who underwent total gastrectomy. To solve those problems, various functional digestive tract reconstruction methods after proximal gastrectomy have been proposed gradually. In order to provide some help for clinical treatment, in this article, we reviewed relevant literature and new clinical developments to compare various kinds of functional digestive tract reconstruction methods after proximal gastrectomy mainly from perioperative outcomes, postoperative quality of life and survival outcomes aspects. After comparison and discussion, we drew the conclusion that various functional reconstruction methods have their own advantages and disadvantages; large scale high-level clinical studies are needed to choose an ideal reconstruction method in the future. Besides, in clinical practice, surgeons should consider the condition of the patient for individualized selection of the most appropriate reconstruction method.

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Improvement of Peripheral Nerve Visualization Using a Deep Learning-based MR Reconstruction Algorithm

10.21203/rs.3.rs-493137/v1 ◽

2021 ◽

Author(s):

Kelly C. Zochowski ◽

Ek Tsoon Tan ◽

Erin C. Argentieri ◽

Bin Lin ◽

Alissa J. Burge ◽

...

Keyword(s):

Deep Learning ◽

Peripheral Nerves ◽

Image Interpretation ◽

Reconstruction Algorithm ◽

Standard Of Care ◽

Interrater Agreement ◽

Reconstruction Method ◽

Reconstruction Methods ◽

Bulk Motion ◽

Mr Reconstruction

Abstract Objective: To assess a new deep learning-based MR reconstruction method, “DLRecon,” for clinical evaluation of peripheral nerves.Methods: Sixty peripheral nerves were prospectively evaluated in 29 patients (mean age: 49±16 years, 17 female) undergoing standard-of-care (SOC) MR neurography for clinically suspected neuropathy. SOC-MRIs and DLRecon-MRIs were obtained through conventional and DLRecon reconstruction methods, respectively. Two radiologists randomly evaluated blinded images for outer epineurium conspicuity, fascicular architecture visualization, pulsation artifact, ghosting artifact, and bulk motion. Results: DLRecon-MRIs were likely to score better than SOC-MRIs for outer epineurium conspicuity (OR=1.9, p=0.007) and visualization of fasicular architecture (OR=1.8, p<0.001) and were likely to score worse for ghosting (OR=2.8, p=0.004) and pulsation artifacts (OR=1.6, p=0.004). There was substantial to almost-perfect inter-reconstruction method agreement (AC=0.73-1.00) and fair to almost-perfect interrater agreement (AC=0.34-0.86) for all features evaluated. DLRecon-MRI had improved interrater agreement for outer epineurium conspicuity (AC=0.71, substantial agreement) compared to SOC-MRIs (AC=0.34, fair agreement). In >80% of images, the radiologist correctly identified an image as SOC- or DLRecon-MRI.Discussion: Outer epineurium and fasicular architecture conspicuity, two key morphological features critical to evaluating a nerve injury, were improved in DLRecon-MRIs compared to SOC-MRIs. Although pulsation and ghosting artifacts increased in DLRecon images, image interpretation was unaffected.

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