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Purpose: Dual ene.g. CT (DeCT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DeCT. existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DeCT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty we.g.t in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of ne.g.boring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the e.g.s in the CT images before decomposition. These e.g. pixels have small we.g.ts in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate.g.adient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those.g.nerated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the prop

关键词： Computed tomography Matrix theory Noise Numerical linear algebra general statistical methods Spatial resolution computerised tomography conjugate.g.adient methods covariance matrices e.g. detection image denoising image resolution iterative methods least squares approximations matrix inversion medical image processing phantoms dual-ene.g. CT image-domain decomposition noise suppression best linear unbiased estimation e.g. predetection Computerised tomographs Biological material, e.g. blood, urine Haemocytometers Digital computing or data processing equipment or methods, specially adapted for specific applications image data processing or generation, in general image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image Medical imaging Medical image noise Computed tomography Medical image reconstruction Medical image spatial resolution Medical X-ray imaging Spatial resolution Matrix inversion Medical image smoothing Density measurement

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erratum: "Three-dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: Comparison with F-18-FDg PeT" [Med. Phys. 41(12), 121904 (2014)]

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Medical physics 2015年第8期42卷 4998页

作者： Thomas Knogler Karem el-Rabadi Michael Weber georgios Karanikas Marius e Mayerhoefer Department of Biomedical Imaging and Image-guided Therapy Medical University of Vienna Vienna 1090 Austria.

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Progressive Cone Beam CT Dose Control in image-guided Radiation Therapy

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MeDICAL PHYSICS 2013年第6期40卷 060701页

作者： Yan, H. Zhen, X. Cervino, L. Jiang, S. Jia, X. Univ Calif San Diego Ctr Adv Radiotherapy Technol San Diego CA 92103 USA Southern Med Univ Guangzhou Guangdong Peoples R China

OBJeCTIVe:Cone beam CT (CBCT) in image-guided radiotherapy (IgRT) offers a tremendous advantage for treatment guidance. The associated imaging dose is a clinical concern. One unique feature of CBCT-based IgRT is that the same patient is repeatedly scanned during a treatment course, and the contents of CBCT images at different fractions are similar. The authors propose a progressive dose control (PDC) scheme to utilize this temporal correlation for imaging dose reduction.;MeTHODS:A dynamic CBCT scan protocol, as opposed to the static one in the current clinical practice, is proposed to gradually reduce the imaging dose in each treatment fraction. The CBCT image from each fraction is processed by a prior-image based nonlocal means (PINLM) module to enhance its quality. The increasing amount of prior information from previous CBCT images prevents degradation of image quality due to the reduced imaging dose. Two proof-of-principle experiments have been conducted using measured phantom data and Monte Carlo simulated patient data with deformation.;ReSULTS:In the measured phantom case, utilizing a prior image acquired at 0.4 mAs, PINLM is able to improve the image quality of a CBCT acquired at 0.2 mAs by reducing the noise level from 34.95 to 12.45 HU. In the synthetic patient case, acceptable image quality is maintained at four consecutive fractions with gradually decreasing exposure levels of 0.4, 0.1, 0.07, and 0.05 mAs. When compared with the standard low-dose protocol of 0.4 mAs for each fraction, an overall imaging dose reduction of more than 60% is achieved.;CONCLUSIONS:PINLM-PDC is able to reduce CBCT imaging dose in IgRT utilizing the temporal correlations among the sequence of CBCT images while maintaining the quality.

关键词： Dose-volume analysis Dosimetry/exposure assessment Monte Carlo methods image enhancement Computed tomography Treatment planning computerised tomography dosimetry image enhancement medical control systems medical image processing Monte Carlo methods phantoms radiation therapy cone beam CT imaging dose nonlocal gPU Computerised tomographs Radiation therapy Digital computing or data processing equipment or methods, specially adapted for specific applications image data processing or generation, in general image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image Medical imaging Cone beam computed tomography Medical image quality image guided radiation therapy Dosimetry Medical image noise Computed tomography Medical image reconstruction Radiation treatment Anatomy

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