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iterative model reconstruction

Kenichiro Hirata, Daisuke Utsunomiya, Masafumi Kidoh, Yoshinori Funama, Seitaro Oda, Hideaki Yuki, Yasunori Nagayama, Yuji Iyama, Takeshi Nakaura, Daisuke Sakabe, Kenichi Tsujita, Yasuyuki Yamashita
We aimed to evaluate the image quality performance of coronary CT angiography (CTA) under the different settings of forward-projected model-based iterative reconstruction solutions (FIRST).Thirty patients undergoing coronary CTA were included. Each image was reconstructed using filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR-3D), and 2 model-based iterative reconstructions including FIRST-body and FIRST-cardiac sharp (CS). CT number and noise were measured in the coronary vessels and plaque...
May 2018: Medicine (Baltimore)
Mun Bae Lee, Hyung Joong Kim, Eung Je Woo, Oh In Kwon
Transcranial direct current stimulation (tDCS) is a widely used non-invasive brain stimulation technique by applying low-frequency weak direct current via electrodes attached on the head. The tDCS using a fixed current between 1 and 2 mA has relied on computational modelings to achieve optimal stimulation effects. Recently, by measuring the tDCS current induced magnetic field using an MRI scanner, the internal current pathway has been successfully recovered. However, up to now, there is no technique to visualize electrical properties including the electrical anisotropic conductivity, effective extracellular ion-concentration, and electric field using only the tDCS current in-vivo...
2018: PloS One
B Liu, S Gao, Z Chang, C Wang, Z Liu, J Zheng
PURPOSE: To evaluate the use of 80 kVp and iterative model reconstruction (IMR) in lower extremity computed tomography angiography (CTA). MATERIALS AND METHODS: Sixty patients were randomly assigned to Group A or Group B (both n=30) to further undergo CTA. Group A received Protocol 1 (P1) with 120 kVp, 180mAs, and 100mL of contrast agent with filtered back-projection (FBP). Group B received Protocol 2 (P2) and Protocol 3 (P3) with 80 kVp, 140mAs and 75mL of contrast agent with hybrid iterative reconstruction (P2) and IMR (P3)...
May 9, 2018: Diagnostic and Interventional Imaging
Paul G M Knoops, Alessandro Borghi, Federica Ruggiero, Giovanni Badiali, Alberto Bianchi, Claudio Marchetti, Naiara Rodriguez-Florez, Richard W F Breakey, Owase Jeelani, David J Dunaway, Silvia Schievano
Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper...
2018: PloS One
Anais Viry, Christoph Aberle, Damien Racine, Jean-François Knebel, Sebastian T Schindera, Sabine Schmidt, Fabio Becce, Francis R Verdun
PURPOSE: To investigate how various generations of iterative reconstruction (IR) algorithms impact low-contrast detectability (LCD) in abdominal computed tomography (CT) for different patient effective diameters, using a quantitative task-based approach. METHODS: Investigations were performed using an anthropomorphic abdominal phantom with two optional additional rings to simulate varying patient effective diameters (25, 30, and 35 cm), and containing multiple spherical targets (5, 6, and 8 mm in diameter) with a 20-HU contrast difference...
April 2018: Physica Medica: PM
Tian Mou, Jian Huang, Finbarr O'Sullivan
The basic emission process associated with positron emission tomography (PET) imaging is Poisson in nature. Reconstructed images inherit some aspects of this-regional variability is typically proportional to the regional mean. Iterative reconstruction using expectation-maximization (EM), widely used in clinical imaging now, imposes positivity constraints that impact noise properties. This paper is motivated by the analysis of data from a physical phantom study of a PET/CT scanner in routine clinical use. Both traditional filtered back-projection (FBP) and EM reconstructions of the images are considered...
May 2018: IEEE Transactions on Medical Imaging
Nienke G Eijsvoogel, Babs M F Hendriks, Hugo B Park, Sibel Altintas, Casper Mihl, Barbora Horehledova, Bastiaan L J H Kietselaer, Harry J G M Crijns, Joachim E Wildberger, Marco Das
Modern high-performance computed tomography (CT) scanners with improved scan acquisition times now allow for routine assessment of cardiac pathologies on chest CTs, which can result in numerous incidental cardiac findings. The CaPaCT study, an observer blinded, single-centre study, aims to assess the visibility, management and possible clinical impact of incidental cardiac pathologies that are now becoming visible on standard chest CTs. A total of 217 consecutive patients referred for a chest CT on a high-performance third-generation dual-source CT scanner will be included...
2018: European radiology experimental
Touko Kaasalainen, Teemu Mäkelä, Anna Kelaranta, Mika Kortesniemi
RATIONALE AND OBJECTIVES: This phantom study aimed to evaluate low-dose (LD) chest computed tomography (CT) protocols using model-based iterative reconstruction (MBIR) for diagnosing lung metastases in patients with sarcoma. MATERIALS AND METHODS: An adult female anthropomorphic phantom was scanned with a 64-slice CT using four LD protocols and a standard-dose protocol. Absorbed organ doses were measured with 10 metal-oxide-semiconductor field-effect transistor dosimeters...
April 30, 2018: Academic Radiology
Shiri Gordon, Irit Dolgopyat, Itamar Kahn, Tammy Riklin Raviv
MRI Segmentation of a pathological brain poses a significant challenge, as the available anatomical priors that provide top-down information to aid segmentation are inadequate in the presence of abnormalities. This problem is further complicated for longitudinal data capturing impaired brain development or neurodegenerative conditions, since the dynamic of brain atrophies has to be considered as well. For these cases, the absence of compatible annotated training examples renders the commonly used multi-atlas or machine-learning approaches impractical...
April 30, 2018: NeuroImage
Tao Yu, Weiwei Cai, Yingzheng Liu
Optical tomography has attracted surged research efforts recently due to the progress in both the imaging concepts and the sensor and laser technologies. The high spatial and temporal resolutions achievable by these methods provide unprecedented opportunity for diagnosis of complicated turbulent combustion. However, due to the high data throughput and the inefficiency of the prevailing iterative methods, the tomographic reconstructions which are typically conducted off-line are computationally formidable. In this work, we propose an efficient inversion method based on a machine learning algorithm, which can extract useful information from the previous reconstructions and build efficient neural networks to serve as a surrogate model to rapidly predict the reconstructions...
April 2018: Review of Scientific Instruments
Yanpeng Cao, Baobei Xu, Zhangyu Ye, Jiangxin Yang, Yanlong Cao, Christel-Loic Tisse, Xin Li
Three-dimensional geometrical models with incorporated surface temperature data provide important information for various applications such as medical imaging, energy auditing, and intelligent robots. In this paper we present a robust method for mobile and real-time 3D thermographic reconstruction through depth and thermal sensor fusion. A multimodal imaging device consisting of a thermal camera and a RGB-D sensor is calibrated geometrically and used for data capturing. Based on the underlying principle that temperature information remains robust against illumination and viewpoint changes, we present a Thermal-guided Iterative Closest Point (T-ICP) methodology to facilitate reliable 3D thermal scanning applications...
April 2, 2018: Optics Express
Logan R Graves, Heejoo Choi, Wenchuan Zhao, Chang Jin Oh, Peng Su, Tianquan Su, Dae Wook Kim
We present a novel model-free iterative data-processing approach that improves surface reconstruction accuracy for deflectometry tests of unknown surfaces. This new processing method iteratively reconstructs the surface, leading to reduced error in the final reconstructed surface. The method was implemented in a deflectometry system, and a freeform surface was tested and compared to interferometric test results. The reconstructed departure from interferometric results was reduced from 15.80 μm RMS with model-based deflectometry down to 5...
May 1, 2018: Optics Letters
Abdulaziz Alhazmi, Chiara Gianoli, Sebastian Neppl, Juliana Martins, Stella Veloza, Mark Podesta, Frank Verhaegen, Michael Reiner, Claus Belka, Katia Parodi
Intensity Modulated Radiation Therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT) are relatively complex treatment delivery techniques and require Quality Assurance (QA) procedures. Pre-treatment dosimetric verification represents a fundamental QA rocedure in daily clinical routine in radiation therapy. The purpose of this study is to develop an EPID-based approach to reconstruct a 3D dose distribution as imparted to a virtual cylindrical water phantom to be used for plan-specific pre-treatment dosimetric verification for IMRT and VMAT plans...
May 1, 2018: Physics in Medicine and Biology
Guillaume Rucher, Lucie Cameliere, Jihene Fendri, Ahmed Abbas, Kevin Dupont, Said Kamel, Nicolas Delcroix, Axel Dupont, Ludovic Berger, Alain Manrique
PURPOSE: The purpose of this study was to assess the impact of positron emission tomography/X-ray computed tomography (PET/CT) acquisition and reconstruction parameters on the assessment of mineralization process in a mouse model of atherosclerosis. PROCEDURES: All experiments were performed on a dedicated preclinical PET/CT system. CT was evaluated using five acquisition configurations using both a tungsten wire phantom for in-plane resolution assessment and a bar pattern phantom for cross-plane resolution...
April 30, 2018: Molecular Imaging and Biology: MIB: the Official Publication of the Academy of Molecular Imaging
Yu Zhao, Fangfei Ge, Tianming Liu
fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional Autoencoder (DCAE). However, interpretations of those decomposed networks are still open questions due to the lack of functional brain atlases, no correspondence across decomposed or reconstructed networks across different subjects, and significant individual variabilities...
April 26, 2018: Medical Image Analysis
André Euler, Justin Solomon, Daniele Marin, Rendon C Nelson, Ehsan Samei
OBJECTIVE: The purpose of this study was to assess image noise, spatial resolution, lesion detectability, and the dose reduction potential of a proprietary third-generation adaptive statistical iterative reconstruction (ASIR-V) technique. MATERIALS AND METHODS: A phantom representing five different body sizes (12-37 cm) and a contrast-detail phantom containing lesions of five low-contrast levels (5-20 HU) and three sizes (2-6 mm) were deployed. Both phantoms were scanned on a 256-MDCT scanner at six different radiation doses (1...
April 27, 2018: AJR. American Journal of Roentgenology
Lorenz Birnbacher, Manuel Viermetz, Wolfgang Noichl, Sebastian Allner, Andreas Fehringer, Mathias Marschner, Maximilian von Teuffenbach, Marian Willner, Klaus Achterhold, Peter B Noël, Thomas Koehler, Julia Herzen, Franz Pfeiffer
Grating-based phase-contrast computed tomography (GBPC-CT) enables increased soft tissue differentiation, but often suffers from streak artifacts when performing high-sensitivity GBPC-CT of biomedical samples. Current GBPC-CT setups consist of one-dimensional gratings and hence allow to measure only the differential phase-contrast (DPC) signal perpendicular to the direction of the grating lines. Having access to the full two-dimensional DPC signal can strongly reduce streak artefacts showing up as characteristic horizontal lines in the reconstructed images...
April 26, 2018: Scientific Reports
X X Liang, L D Liang, Y Y Zhang, J B Gao, Y G Zhang, X Liu, Q Chi
Objective: To quantitatively evaluate the quality of advanced modeled iterative reconstruction (ADMIRE) combined with 70 kVp and linear blending images in low dose dual energy (70 kVp/sn150 kVp) pulmonary angiography. Methods: A total of 74 cases with normal BMI underwent dual-source CT dual-energy pulmonary angiography with small amount of contrast medium (30 ml) from 2015 to 2017 from the First Affiliated Hospital of Zhengzhou University were randomly assigned to protocol Ⅰ(100 kVp/sn140 kVp) or protocol Ⅱ(70 kVp/sn150 kVp)...
April 3, 2018: Zhonghua Yi Xue za Zhi [Chinese medical journal]
Junfeng Wu, Fang Dai, Gang Hu, Xuanqin Mou
Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Recently, statistical iterative reconstruction (SIR) with l0-norm dictionary learning regularization has been developed to reconstruct CT images from the low dose and few-view dataset in order to reduce radiation dose. Nonetheless, the sparse regularization term adopted in this approach is l0-norm, which cannot guarantee the global convergence of the proposed algorithm...
April 18, 2018: Journal of X-ray Science and Technology
Sun Zheng, Zheng Lan
Intravascular photoacoustic (IVPA) imaging can discriminate between normal arterial tissues and atheromatous plaques in images, particularly images of lipid-rich plaques with high spatial resolution and optical contrast. However, conventional IVPA only recovers the deposited optical energy that is the product of the tissue optical absorption coefficient and local optical fluence. Herein, a one-step model-based method for single-wavelength IVPA imaging system is proposed. The proposed method directly reconstructs the optical absorption coefficient from the boundary measurement of acoustic pressure...
April 21, 2018: Computers in Biology and Medicine
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