scholarly journals CT Metal Artifact Reduction Method Based on Improved Image Segmentation and Sinogram In-Painting

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Yang Chen ◽  
Yinsheng Li ◽  
Hong Guo ◽  
Yining Hu ◽  
Limin Luo ◽  
...  
Keyword(s):  
Image Quality ◽  
Large Scale ◽  
Projection Data ◽  
Metal Artifacts ◽  
Metal Implants ◽  
Local Means ◽  
Corrected Image ◽  
Streak Artifacts ◽  
New Strategy ◽  
Stage Process

The streak artifacts caused by metal implants degrade the image quality and limit the applications of CT imaging. The standard method used to reduce these metallic artifacts often consists of interpolating the missing projection data but the result is often a loss of image quality with additional artifacts in the whole image. This paper proposes a new strategy based on a three-stage process: (1) the application of a large-scale non local means filter (LS-NLM) to suppress the noise and enhance the original CT image, (2) the segmentation of metal artifacts and metallic objects using a mutual information maximized segmentation algorithm (MIMS), (3) a modified exemplar-based in-painting technique to restore the corrupted projection data in sinogram. The final corrected image is then obtained by merging the segmented metallic object image with the filtered back-projection (FBP) reconstructed image from the in-painted sinogram. Quantitative and qualitative experiments have been conducted on both a simulated phantom and clinical CT images and a comparative study has been led with Bal's algorithm that proposed a similar segmentation-based method.

scholarly journals Metal artifacts in intraoperative O-arm CBCT scans

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Juha I. Peltonen ◽  
Touko Kaasalainen ◽  
Mika Kortesniemi
Keyword(s):  
Image Quality ◽  
Imaging Modality ◽  
Nonlinear Effects ◽  
Exposure Level ◽  
Metal Artifacts ◽  
Imaging Protocol ◽  
Metal Implants ◽  
Comprehensive Determination

Abstract Background Cone-beam computed tomography (CBCT) has become an increasingly important medical imaging modality in orthopedic operating rooms. Metal implants and related image artifacts create challenges for image quality optimization in CBCT. The purpose of this study was to develop a robust and quantitative method for the comprehensive determination of metal artifacts in novel CBCT applications. Methods The image quality of an O-arm CBCT device was assessed with an anthropomorphic pelvis phantom in the presence of metal implants. Three different kilovoltage and two different exposure settings were used to scan the phantom both with and without the presence of metal rods. Results The amount of metal artifact was related to the applied CBCT imaging protocol parameters. The size of the artifact was moderate with all imaging settings. The highest applied kilovoltage and exposure level distinctly increased artifact severity. Conclusions The developed method offers a practical and robust way to quantify metal artifacts in CBCT. Changes in imaging parameters may have nonlinear effects on image quality which are not anticipated based on physics.

scholarly journals Intraoperative Myelography in Cervical Multilevel Stenosis Using 3D Rotational Fluoroscopy: Assessment of Feasibility and Image Quality

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Thomas Westermaier ◽  
Stefan Koehler ◽  
Thomas Linsenmann ◽  
Michael Kiderlen ◽  
Paul Pakos ◽  
...  
Keyword(s):  
Image Quality ◽  
Water Soluble ◽  
Operating Table ◽  
Metal Artifacts ◽  
Residual Stenosis ◽  
Cervical Myelography ◽  
Metal Implants ◽  
3D Fluoroscopy ◽  
Anterior Corpectomy

Background. Intraoperative myelography has been reported for decompression control in multilevel lumbar disease. Cervical myelography is technically more challenging. Modern 3D fluoroscopy may provide a new opportunity supplying multiplanar images. This study was performed to determine the feasibility and image quality of intraoperative cervical myelography using a 3D fluoroscope.Methods. The series included 9 patients with multilevel cervical stenosis. After decompression, 10 mL of water-soluble contrast agent was administered via a lumbar drainage and the operating table was tilted. Thereafter, a 3D fluoroscopy scan (O-Arm) was performed and visually evaluated.Findings. The quality of multiplanar images was sufficient to supply information about the presence of residual stenosis. After instrumentation, metal artifacts lowered image quality. In 3 cases, decompression was continued because myelography depicted residual stenosis. In one case, anterior corpectomy was not completed because myelography showed sufficient decompression after 2-level discectomy.Interpretation. Intraoperative myelography using 3D rotational fluoroscopy is useful for the control of surgical decompression in multilevel spinal stenosis providing images comparable to postmyelographic CT. The long duration of contrast delivery into the cervical spine may be solved by preoperative contrast administration. The method is susceptible to metal artifacts and, therefore, should be applied before metal implants are placed.

scholarly journals Short loop functional commonality identified in leukaemia proteome highlights crucial protein sub-networks

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Sun Sook Chung ◽  
Joseph C F Ng ◽  
Anna Laddach ◽  
N Shaun B Thomas ◽  
Franca Fraternali
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Short Loop ◽  
New Strategy ◽  
Loop Network ◽  
Protein Protein Interaction Network

Abstract Direct drug targeting of mutated proteins in cancer is not always possible and efficacy can be nullified by compensating protein–protein interactions (PPIs). Here, we establish an in silico pipeline to identify specific PPI sub-networks containing mutated proteins as potential targets, which we apply to mutation data of four different leukaemias. Our method is based on extracting cyclic interactions of a small number of proteins topologically and functionally linked in the Protein–Protein Interaction Network (PPIN), which we call short loop network motifs (SLM). We uncover a new property of PPINs named ‘short loop commonality’ to measure indirect PPIs occurring via common SLM interactions. This detects ‘modules’ of PPI networks enriched with annotated biological functions of proteins containing mutation hotspots, exemplified by FLT3 and other receptor tyrosine kinase proteins. We further identify functional dependency or mutual exclusivity of short loop commonality pairs in large-scale cellular CRISPR–Cas9 knockout screening data. Our pipeline provides a new strategy for identifying new therapeutic targets for drug discovery.

scholarly journals First experience with combined use of adaptive statistical iterative reconstruction and gemstone spectral imaging in spinal fusion CT images

2015 ◽  
Author(s):  
Fengdan Wang ◽  
Yan Zhang ◽  
Zhengyu Jin ◽  
Richard Zwar
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Dual Energy ◽  
Dual Energy Ct ◽  
Metal Artifacts ◽  
Adaptive Statistical Iterative Reconstruction ◽  
Subjective Image Quality ◽  
Gemstone Spectral Imaging ◽  
Statistical Iterative Reconstruction ◽  
Combined Use

Objective. To explore whether the image noises and the metal artifacts could be further managed by the combined use of two technologies, the adaptive statistical iterative reconstruction (ASIR) and the monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. Materials and Methods. Fifty-one patients with 318 spinal pedicle screws were prospectively scanned with dual energy CT by using fast kV-switching GSI between 80 and 140 kVp. The monochromatic GSI images at 110 keV were reconstructed either without ASIR or with ASIR of various levels (30%, 50%, 70% and 100%). For these five sets of images, both objective and subjective image quality assessments were performed to evaluate the image quality. Results. With objective image quality assessment, the metal artifacts (measured by an artifacts index) significantly decreased when increasing levels of ASIR was utilized (p < 0.001). Moreover, adding ASIR to GSI also decreased the image noise (p < 0.001) and improved the signal-to-noise ratio (SNR, p < 0.001). With subjective image quality analysis, the inter-reader agreements were good, with intra-class correlation coefficients (ICC) of 0.89 to 0.99. Meanwhile, the visualization of the peri-implant soft tissue was improved at higher ASIR levels (p < 0.001). Conclusion. Combined use of ASIR and GSI is shown to decrease the image noise and improve the image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels of over 70%.

Projection-to-image transform frame: a lightweight block reconstruction network (LBRN) for computed tomography

2021 ◽  
Author(s):  
Genwei Ma ◽  
Xing Zhao ◽  
Yining Zhu ◽  
Huitao Zhang
Keyword(s):  
Neural Network ◽  
Computed Tomography ◽  
Real Data ◽  
Projection Data ◽  
Ct Reconstruction ◽  
Back Projection ◽  
Image Block ◽  
Metal Artifacts ◽  
Reconstruction Process ◽  
Memory Space

Abstract To solve the problem of learning based computed tomography (CT) reconstruction, several reconstruction networks were invented. However, applying neural network to tomographic reconstruction still remains challenging due to unacceptable memory space requirement. In this study, we presents a novel lightweight block reconstruction network (LBRN), which transforms the reconstruction operator into a deep neural network by unrolling the filter back-projection (FBP) method. Specifically, the proposed network contains two main modules, which, respectively, correspond to the filter and back-projection of FBP method. The first module of LBRN decouples the relationship of Radon transform between the reconstructed image and the projection data. Therefore, the following module, block back-projection module, can use the block reconstruction strategy. Due to each image block is only connected with part filtered projection data, the network structure is greatly simplified and the parameters of the whole network is dramatically reduced. Moreover, this approach is trained end-to-end, working directly from raw projection data and does not depend on any initial images. Five reconstruction experiments are conducted to evaluate the performance of the proposed LBRN: full angle, low-dose CT, region of interest (ROI), metal artifacts reduction and real data experiment. The results of the experiments show that the LBRN can be effectively introduced into the reconstruction process and has outstanding advantages in terms of different reconstruction problems.

Precise No-Reference Image Quality Evaluation Based on Distortion Identification

2021 ◽  
Vol 17 (3s) ◽  
pp. 1-21
Author(s):  
Chenggang Yan ◽  
Tong Teng ◽  
Yutao Liu ◽  
Yongbing Zhang ◽  
Haoqian Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Quality Assessment ◽  
Large Scale ◽  
Quality Evaluation ◽  
Image Quality Assessment ◽  
State Of The Art ◽  
Gaussian White Noise ◽  
The State ◽  
Reference Image

The difficulty of no-reference image quality assessment (NR IQA) often lies in the lack of knowledge about the distortion in the image, which makes quality assessment blind and thus inefficient. To tackle such issue, in this article, we propose a novel scheme for precise NR IQA, which includes two successive steps, i.e., distortion identification and targeted quality evaluation. In the first step, we employ the well-known Inception-ResNet-v2 neural network to train a classifier that classifies the possible distortion in the image into the four most common distortion types, i.e., Gaussian white noise (WN), Gaussian blur (GB), jpeg compression (JPEG), and jpeg2000 compression (JP2K). Specifically, the deep neural network is trained on the large-scale Waterloo Exploration database, which ensures the robustness and high performance of distortion classification. In the second step, after determining the distortion type of the image, we then design a specific approach to quantify the image distortion level, which can estimate the image quality specially and more precisely. Extensive experiments performed on LIVE, TID2013, CSIQ, and Waterloo Exploration databases demonstrate that (1) the accuracy of our distortion classification is higher than that of the state-of-the-art distortion classification methods, and (2) the proposed NR IQA method outperforms the state-of-the-art NR IQA methods in quantifying the image quality.

scholarly journals Assessment of 4D Ultrasound Systems for Image-guided Radiation Therapy – Image Quality, Framerates and CT Artifacts

2019 ◽  
Vol 5 (1) ◽  
pp. 245-248
Author(s):  
Svenja Ipsen ◽  
Ralf Bruder ◽  
Verónica García-Vázquez ◽  
Achim Schweikard ◽  
Floris Ernst
Keyword(s):  
Radiation Therapy ◽  
Image Quality ◽  
Image Guidance ◽  
State Of The Art ◽  
Clinical Performance ◽  
Clinical Implementation ◽  
Metal Artifacts ◽  
Image Guided Radiation Therapy ◽  
4D Ultrasound ◽  
Matrix Array

Abstract4D ultrasound (4D US) is gaining relevance as a tracking method in radiation therapy (RT) with modern matrix array probes offering new possibilities for real-time target detection. However, for clinical implementation of USguided RT, image quality, volumetric framerate and artifacts caused by the probe’s presence during planning and / or setup computed tomography (CT) must be quantified. We compared three diagnostic 4D US systems with matrix array probes using a commercial wire phantom to measure spatial resolution as well as a calibration and a torso phantom to assess different image quality metrics. CT artifacts were quantified in the torso phantom by calculating the total variation and percentage of affected voxels between a reference CT scan and CT scans with probes in place. We found that state-of-the-art 4D US systems with small probes can fit inside the CT bore and cause fewer metal artifacts than larger probes. US image quality varies between systems and is task-dependent. Volume sizes and framerates are much higher than the commercial guidance solution for US-guided RT, warranting further investigation regarding clinical performance for image guidance.

scholarly journals Underground parking lot at Turku market square - Zero energy parking hall and the biggest solar energy storage in the world

2020 ◽  
Vol 172 ◽  
pp. 16008
Author(s):  
Rauli Lautkankare ◽  
Nikolas Salomaa ◽  
Birgitta Martinkauppi ◽  
Anna Slobodenyuk
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Solar Thermal Energy ◽  
Global Environmental ◽  
The World ◽  
New Strategy ◽  
Parking Lot ◽  
Zero Carbon ◽  
Carbon Neutral ◽  
Technical Solutions

This paper opens the case Turku market square underground parking lot from the energy perspective. Also constructional and historical aspects are presented. Heavily populated city center has faced several challenges, such as intense traffic. Uncomfortable local tailpipe emissions and lack of parking spaces have decreased living conditions for the citizens and visitors. Therefore, total renovation of main market square of Turku was started in autumn 2018. Together with that, municipality should respond not only to primary needs, but also to national and global environmental targets. One of the new strategy objectives for Turku is being carbon-neutral city by 2029. Hence, project was based on large-scale renewable resources utilization for urban underground spaces. Research and analysis of possible technical solutions was made. Modern time is characterized by climate change and strong measures that need to be taken to stop the global warming. The heat, cold and electricity should be produced in a carbon neutral manner. This doesn’t exclude heated multilevel car parking facilities either. As the parking capacity grows and finding a free place is easier, a positive environmental effect is expected to be reached. The described underground parking lot in Turku is first of its kind in many ways: 1) Never before underground parking lot has dug up and constructed into clay-based soils in Finland, 2) it is probably the first zero carbon energy parking hall in Europe and 3) it has the biggest solar thermal energy storage in the world.

scholarly journals Metal artifact correction strategies in MRI-based attenuation correction in PET/MRI

BJR|Open ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 20190033 ◽  
Author(s):  
Georg Schramm ◽  
Claes Nøhr Ladefoged
Keyword(s):  
Image Quality ◽  
Attenuation Correction ◽  
The Body ◽  
Metal Artifact ◽  
Metal Artifacts ◽  
Artifact Correction ◽  
Positron Emission ◽  
Pet Image Reconstruction ◽  
The Impact ◽  
Correction Strategies

In hybrid positron emission tomography (PET) and MRI systems, attenuation correction for PET image reconstruction is commonly based on processing of dedicated MR images. The image quality of the latter is strongly affected by metallic objects inside the body, such as e.g. dental implants, endoprostheses, or surgical clips which all lead to substantial artifacts that propagate into MRI-based attenuation images. In this work, we review publications about metal artifact correction strategies in MRI-based attenuation correction in PET/MRI. Moreover, we also give an overview about publications investigating the impact of MRI-based attenuation correction metal artifacts on the reconstructed PET image quality and quantification.

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