Filtered Backprojection Method Research Articles

Quantitative and Qualitative Evaluations of Defect Images in Different Regions of Myocardial Phantom under Implementation of Various Filters in SPECT

In myocardial perfusion single Photon Emission Computed Tomography (SPECT), images are degraded by photon attenuation, distance-dependent collimator, detector response. The filters in reconstruction process can greatly affect the quality of the SPECT images. The purpose of this study is to make quantitative and qualitative evaluation of the acquired SPECT images of similar defects which are located in the different regions of myocardial phantom under implementation of different filters. Herein, rectangular defects with the same thickness were inserted on the different regions of on the inner wall of the myocardial phantom. Myocardial perfusion study was performed with meta-stable Technetium with a dual head SPECT system. Raw data was reconstructed by filter back projection method with some filters. Then, results of implementation of various filters with different parameters on the contrast, signal to noise ratio and size of defects images in transverse, coronal and sagittal views of the phantom have been studied. The results show that contrast, signal to noise ratio and size of defects images are depending on the defect locations, type of filters and the selection of view which is examined for specified defect.

SU-E-I-35: Development of Stand-Alone Filtered Backprojection and Iterative Reconstruction Methods Using the Raw CT Data Exported From Clinical Lung Screening Scans

Purpose: We are developing a research pipeline for generating CT image series that represent a wide variety of acquisition and reconstruction conditions. As part of this effort, we need stand-alone filtered backprojection (FBP) and iterative reconstruction methods that: (1) can operate on the raw CT data from clinical scans and (2) can be integrated into an acquisition/reconstruction pipeline for evaluating effects of acquisition and reconstruction settings on Quantitative Imaging metrics and CAD algorithms. Methods: Two reconstruction methods were developed: (1) a weighted FBP method, and (2) an iterative method based on sequential minimization of a penalized least-squares objective function (i.e. iterative coordinate descent). Both methods were adapted from previously-published algorithms. Using information about the raw CT data format obtained through a research agreement with Siemens Healthcare, we extracted the sinogram from a low-dose lung screening case acquired on a Sensation 64 scanner as part of the National Lung Screening Trial. We reconstructed the raw data on the scanner with a B50 kernel and again with each of our standalone reconstruction methods. A relatively sharp kernel was used in our FBP method to match the appearance of the B50 kernel. The iterative method used a regularization parameter of 1 and a stopping criterion of 200 iterations. The reconstructed field of view was 29 cm for all methods. Results: Reconstructed images from our FBP method agreed very well with images reconstructed at the scanner. Computation speed was a limiting factor for the iterative method, but initial downsampled results and images of a thin slab of the scanned volume demonstrated substantial potential. Various artifacts should be addressed before direct comparisons of image quality can be made. Conclusion: Our stand-alone FBP and iterative reconstruction methods show potential for developing a general acquisition/reconstruction research pipeline that can be applied to Quantitative Imaging and CAD applications. NCI grant U01 CA181156 (Quantitative Imaging Network) and Tobacco Related Disease Research Project grant 22RT-0131.

Tomographic phase microscopy with 180° rotation of live cells in suspension by holographic optical tweezers.

We present a new tomographic phase microscopy (TPM) approach that allows capturing the three-dimensional refractive index structure of single cells in suspension without labeling, using 180° rotation of the cells. This is obtained by integrating an external off-axis interferometer for wide-field wave front acquisition with holographic optical tweezers (HOTs) for trapping and micro-rotation of the suspended cells. In contrast to existing TPM approaches for cell imaging, our approach does not require anchoring the sample to a rotating stage, nor is it limited in angular range as is the illumination rotation approach. Thus, it allows noninvasive TPM of suspended live cells in a wide angular range. The proposed technique is experimentally demonstrated by capturing the three-dimensional refractive index map of yeast cells, while collecting interferometric projections at an angular range of 180° with 5° steps. The interferometric projections are processed by both the filtered back-projection method and the diffraction theory method. The experimental system is integrated with a spinning disk confocal fluorescent microscope for validation of the label-free TPM results.

Projection-Wise Filter Optimization for Limited-Angle Cone-Beam CT Using the Approximate Inverse

In this paper, we present a novel and efficient approach for the optimization of filters for limited-angle cone beam computed tomography (CBCT). Our method is based on the theory of approximate inverse (AI) and uses a simultaneous iterative reconstruction technique (SIRT) to estimate a view-dependent reconstruction kernel. From this kernel we then derive a set of 2-D filters that can be applied in a filtered backprojection (FBP) algorithm. By construction the resulting filters are independent of the measured data, so that they can be precomputed for a given geometric setup and be reused with different projection datasets. Our approach is the first application of the AI for 3-D limited-angle CBCT supported by iterative reconstruction, such that in comparison to existing methods, it does not rely on additional reference measurements or on the existence of an analytical inversion formula. However, our method reaches results better than standard FBP methods. Additionally, we provide a general scheme that allows the transfer of our method to other system geometries and gives us the ability to extend it with more complex filters. We will conduct several experiments with simulated and real data where we examine the image quality of our method in comparison to standard FBP and SIRT. The results will show that our angle-optimized FBP has a higher contrast-to-artifact ratio than FBP. In addition to this, we analyze the image quality perpendicular to the in-focus plane by the use of the artifact spread function and show that our technique can be employed to reduce the amount of ghosting artifacts.

Development of simple processing for deleting undershooting artifact using the FBP method ─evaluation of simulation data─

The undershooting artifact occurs using the filtered back projection (FBP) method. This artifact is influenced by a ramp filter. Thereby, the fall of the target accumulation and a deficit arise and it becomes a clinical problem. We developed a new image reconstruction method based on the FBP method to delete the undershooting artifact of FBP. The image quality of the FBP method is equivalent to that obtained by an evaluation using a digital phantom. The two segmentation and ordinary FBP methods were evaluated in terms of hot contrast, cold contrast, coefficient of variation (%CV), and root mean square uncertainty (%RSMU). The two segmentation FBP method showed equivalent values of hot contrast, % CV, and% RSMU compared with those of the ordinary FBP method. With a threshold level value, cold contrast sharply changed. However, when the threshold level of the two segmentation FBP method was set as the proper value, 90% contrast was obtained. It is necessary to set a threshold level as a proper value using the two segmentation FBP methods. I thought that it can delete an artifact in a simple way, without impairing the image quality. However, it is an examination of only a digital phantom this time. Before using it clinically, one has to use and verify a real phantom.

Development of Ultra-low Field SQUID-MRI System with an LC Resonator

We are developing an Ultra-Low Field (ULF) magnetic resonance imaging (MRI) system using high temperature superconductor (HTS)-rf-superconducting quantum interference device (SQUID) for food inspection. The advantage of the ULF MRI system is that non-magnetic contaminants, which are difficult to be detected by a magnetic sensor, can be detected and localized. The system uses HTS-SQUID with high sensitivity that is independent of frequency, because the signal frequency is reduced in ULF. However the detection area of HTS-SQUID is difficult to be increased. Therefore, we studied to increase the detection area using an LC resonator. The LC resonator is composed of a coil (22.9 mH, Φ40mm inner diameter) and a capacitor (the setting resonance frequency of 1890Hz). The signal is detected by a copper wound coil of the resonator, and transferred to HTS-SQUID that inductively coupled to the coil immersed in liquid nitrogen at 77K. We combined the LC resonator with the ULF MRI system, and obtained the 2D-MR images. The signal detector, with the SQUID and the LC resonator, provided a 1.5 times larger detection area. The size of 2D-MR image was near the size of the actual sample. Then we obtained 2D-MR images by a filtered back projection (FBP) method and a 2D-fast fourier transform (FFT) method. In the 2D-FFT method, the pixel size of the image was smaller than that of image by FBP method. As a result, the quality of the 2D-MR image by 2D-FFT method has been improved. There results suggested that the system we are proposing is feasible.

Usefulness of Iterative Reconstruction Method in the Field of Acute Cerebral Infarction Computed Tomography Examination

We evaluated clinical images to investigate the usefulness of adaptive iterative dose reduction algorithm (AIDR) in the field of acute cerebral infarction. We did receiver operating characteristic (ROC) analysis by 4 radiologists using 50 clinical images (abnormal case=24, normal case=26) which were reconstructed by AIDR and filtered back projection (FBP). The area under the curve (AUC) value from average ROC curve of observers were 0.79 with the FBP and 0.87 with the AIDR (P=0.31). The standard deviation of AUC was 0.06 with the FBP and 0.03 with the AIDR. More in detail, the AUC value of Expert group (over 10 years of experience) increased to 0.06 by using AIDR compared with FBP method. On the other hand, in Beginner group (less than 10 years of experience) there was 0.09 increase. Therefore, there was some possibility to reduce the variation of diagnostic accuracy among observer and the diagnostic accuracy improvement of the doctor in a few Experience group, by using AIDR for acute cerebral infarction computed tomography (CT) examination.

Examination of Visual Effect in Low-dose Cerebral CT Perfusion Phantom Image Using Iterative Reconstruction

CT perfusion (CTP) is obtained cerebrovascular circulation image for assessment of stroke patients; however, at the expense of increased radiation dose by dynamic scan. Iterative reconstruction (IR) method is possible to decrease image noise, it has the potential to reduce radiation dose. The purpose of this study is to assess the visual effect of IR method by using a digital perfusion phantom. The digital perfusion phantom was created by reconstructed filtered back projection (FBP) method and IR method CT images that had five exposure doses. Various exposure dose cerebral blood flow (CBF) images were derived from deconvolution algorithm. Contrast-to-noise ratio (CNR) and visual assessment were compared among the various exposure dose and each reconstructions. Result of low exposure dose with IR method showed, compared with FBP method, high CNR in severe ischemic area, and visual assessment was significantly improvement. IR method is useful for improving image quality of low-dose CTP.

Generalized Fourier slice theorem for cone-beam image reconstruction.

The cone-beam reconstruction theory has been proposed by Kirillov in 1961, Tuy in 1983, Feldkamp in 1984, Smith in 1985, Pierre Grangeat in 1990. The Fourier slice theorem is proposed by Bracewell 1956, which leads to the Fourier image reconstruction method for parallel-beam geometry. The Fourier slice theorem is extended to fan-beam geometry by Zhao in 1993 and 1995. By combining the above mentioned cone-beam image reconstruction theory and the above mentioned Fourier slice theory of fan-beam geometry, the Fourier slice theorem in cone-beam geometry is proposed by Zhao 1995 in short conference publication. This article offers the details of the derivation and implementation of this Fourier slice theorem for cone-beam geometry. Especially the problem of the reconstruction from Fourier domain has been overcome, which is that the value of in the origin of Fourier space is 0/0. The 0/0 type of limit is proper handled. As examples, the implementation results for the single circle and two perpendicular circle source orbits are shown. In the cone-beam reconstruction if a interpolation process is considered, the number of the calculations for the generalized Fourier slice theorem algorithm is <formula>O(N^4)</formula>, which is close to the filtered back-projection method, here N is the image size of 1-dimension. However the interpolation process can be avoid, in that case the number of the calculations is O(N5).

High-Resolution and Quantitative X-Ray Phase-Contrast Tomography for Mouse Brain Research.

Imaging techniques for visualizing cerebral vasculature and distinguishing functional areas are essential and critical to the study of various brain diseases. In this paper, with the X-ray phase-contrast imaging technique, we proposed an experiment scheme for the ex vivo mouse brain study, achieving both high spatial resolution and improved soft-tissue contrast. This scheme includes two steps: sample preparation and volume reconstruction. In the first step, we use heparinized saline to displace the blood inside cerebral vessels and then replace it with air making air-filled mouse brain. After sample preparation, X-ray phase-contrast tomography is performed to collect the data for volume reconstruction. Here, we adopt a phase-retrieval combined filtered backprojection method to reconstruct its three-dimensional structure and redesigned the reconstruction kernel. To evaluate its performance, we carried out experiments at Shanghai Synchrotron Radiation Facility. The results show that the air-tissue structured cerebral vasculatures are highly visible with propagation-based phase-contrast imaging and can be clearly resolved in reconstructed cross-images. Besides, functional areas, such as the corpus callosum, corpus striatum, and nuclei, are also clearly resolved. The proposed method is comparable with hematoxylin and eosin staining method but represents the studied mouse brain in three dimensions, offering a potential powerful tool for the research of brain disorders.

Rapid mapping of visual receptive fields by filtered back projection: application to multi-neuronal electrophysiology and imaging.

Neurons in the visual system vary widely in the spatiotemporal properties of their receptive fields (RFs), and understanding these variations is key to elucidating how visual information is processed. We present a new approach for mapping RFs based on the filtered back projection (FBP), an algorithm used for tomographic reconstructions. To estimate RFs, a series of bars were flashed across the retina at pseudo-random positions and at a minimum of five orientations. We apply this method to retinal neurons and show that it can accurately recover the spatial RF and impulse response of ganglion cells recorded on a multi-electrode array. We also demonstrate its utility for in vivo imaging by mapping the RFs of an array of bipolar cell synapses expressing a genetically encoded Ca2+ indicator. We find that FBP offers several advantages over the commonly used spike-triggered average (STA): (i) ON and OFF components of a RF can be separated; (ii) the impulse response can be reconstructed at sample rates of 125 Hz, rather than the refresh rate of a monitor; (iii) FBP reveals the response properties of neurons that are not evident using STA, including those that display orientation selectivity, or fire at low mean spike rates; and (iv) the FBP method is fast, allowing the RFs of all the bipolar cell synaptic terminals in a field of view to be reconstructed in under 4 min. Use of the FBP will benefit investigations of the visual system that employ electrophysiology or optical reporters to measure activity across populations of neurons.

Image reconstruction for digital breast tomosynthesis (DBT) by using projection-angle-dependent filter functions

Digital breast tomosynthesis (DBT) is considered in clinics as a standard three-dimensional imaging modality, allowing the earlier detection of cancer. It typically acquires only 10–30 projections over a limited angle range of 15–60° with a stationary detector and typically uses a computationally-efficient filtered-backprojection (FBP) algorithm for image reconstruction. However, a common FBP algorithm yields poor image quality resulting from the loss of average image value and the presence of severe image artifacts due to the elimination of the dc component of the image by the ramp filter and to the incomplete data, respectively. As an alternative, iterative reconstruction methods are often used in DBT to overcome these difficulties, even though they are still computationally expensive. In this study, as a compromise, we considered a projection-angle-dependent filtering method in which one-dimensional geometry-adapted filter kernels are computed with the aid of a conjugate-gradient method and are incorporated into the standard FBP framework. We implemented the proposed algorithm and performed systematic simulation works to investigate the imaging characteristics. Our results indicate that the proposed method is superior to a conventional FBP method for DBT imaging and has a comparable computational cost, while preserving good image homogeneity and edge sharpening with no serious image artifacts.

Effect of iterative reconstruction algorithms on peripheral MDCT angiography virtual histology plaque volumes: have we been overestimating disease burden?

Our objective was to compare plaque volumes of multidetector computed tomographic images reconstructed using adaptive statistical iterative reconstruction (ASIR), model-based iterative reconstruction (MBIR), and filtered back projection (FBP). We reviewed 25 patients for a total of 50 extremities imaged on the same scanner. Calcified plaque FBP volume (3468.2±2634.8 mm3) was higher than ASIR (2548.1±2166.5 mm3). Calcified plaque FBP volume was higher than MBIR (mean=2345.7±1935.4 mm3). Our findings suggest that traditional FBP methods overestimate disease compared to newer reconstruction methods.

SU-D-BRF-04: Digital Tomosynthesis for Improved Daily Setup in Treatment of Liver Lesions

Purpose: Daily localization of liver lesions with cone-beam CT (CBCT) is difficult due to poor image quality caused by scatter, respiratory motion, and the lack of radiographic contrast between the liver parenchyma and the lesion(s). Digital tomosynthesis (DTS) is investigated as a modality to improve liver visualization and lesion/parenchyma contrast for daily setup. Methods: An in-house tool was developed to generate DTS images using a point-by-point filtered back-projection method from on-board CBCT projection data. DTS image planes are generated in a user defined orientation to visualize the anatomy at various depths. Reference DTS images are obtained from forward projection of the planning CT dataset at each projection angle. The CBCT DTS image set can then be registered to the reference DTS image set as a means for localization. Contour data from the planning CT's associate RT Structure file and forward projected similarly to the planning CT data. DTS images are created for each contoured structure, which can then be overlaid onto the DTS images for organ volume visualization. Results: High resolution DTS images generated from CBCT projections show fine anatomical detail, including small blood vessels, within the patient. However, the reference DTS images generated from forward projection of the planningmore » CT lacks this level of detail due to the low resolution of the CT voxels as compared to the pixel size in the projection images; typically 1mm-by-1mm-by-3mm (lat, vrt, lng) for the planning CT vs. 0.4mm-by-0.4mm for CBCT projections. Overlaying of the contours onto the DTS image allows for visualization of structures of interest. Conclusion: The ability to generate DTS images over a limited range of projection angles allows for reduction in the amount of respiratory motion within each acquisition. DTS may provide improved visualization of structures and lesions as compared to CBCT for highly mobile tumors.« less

SU-D-17A-03: 5D Respiratory Motion Model Based Iterative Reconstruction Method for 4D Cone-Beam CT

Purpose: The purpose of this work is to develop a new iterative reconstruction method for 4D cone-beam CT (CBCT) based on a published time-independent 5D respiratory motion model. The proposed method will offer a single high-resolution image at a user-selected breathing phase and the 5D motion model parameters, which could be used to generate the breathing pattern during the CT acquisition. Methods: 5D respiratory motion model was proposed for accurately modeling the motion of lung and lung tumor tissues. 4D images are then parameterized by a reference image, measured breathing amplitude, breathing rate, two time-independent vector fields that describe the 5D model parameters, and a scalar field that describes the change in HU as a function of breathing amplitude. In contrast with the traditional method of reconstructing multiple temporal image phases to reduce respiratory artifact, 5D model based method simplify the problem into the reconstruction of a single reference image and the 5D motion model parameters. The reconstruction formulation of the reference image and scalar and vector fields is a nonlinear least-square optimization problem that consists of solving the reference image and fields alternately, in which the reference image is regularized with the total variation sparsity transform and the vector fields are solved through linearizations regularized by the H1 norm. 2D lung simulations were performed in this proof-of-concept study. Results: The breathing amplitude, its rate, and the corresponding scalar and vector fields were generated from a patient case. Compared with filtered backprojection method and sparsity regularized iterative method for the phase-by-phase reconstruction, the proposed 5D motion model based method yielded improved image quality. Conclusion: Based on 5D respiratory motion model, we have developed a new iterative reconstruction method for 4D CBCT that has the potential for improving image quality while providing needed on-table motion information.

Development of a system for magnetic particle imaging using neodymium magnets and gradiometer

We developed a system for magnetic particle imaging (MPI) using two opposing neodymium magnets for generating a magnetic-field-free line (FFL) and a gradiometer coil for receiving signals generated by magnetic nanoparticles (MNPs). The projection data were acquired by rotating and translating both a phantom and a gradiometer coil simultaneously, and transverse images were reconstructed using the filtered backprojection (FBP) method and maximum likelihood-expectation maximization (ML-EM) algorithm. The gradiometer coil was superior to a simple solenoid coil in terms of the linearity between the signal intensity and concentration of MNPs and of the robustness against feedthrough interference. The image quality was improved using the ML-EM algorithm compared with using the FBP method; in particular, the number of streak artifacts was reduced. Our preliminary results suggest that our system is useful for realizing MPI with an FFL-encoding scheme and that the ML-EM algorithm is useful for improving the image quality of MPI.

Statistical image reconstruction for low-dose CT using nonlocal means-based regularization

Low-dose computed tomography (CT) imaging without sacrifice of clinical tasks is desirable due to the growing concerns about excessive radiation exposure to the patients. One common strategy to achieve low-dose CT imaging is to lower the milliampere-second (mAs) setting in data scanning protocol. However, the reconstructed CT images by the conventional filtered back-projection (FBP) method from the low-mAs acquisitions may be severely degraded due to the excessive noise. Statistical image reconstruction (SIR) methods have shown potentials to significantly improve the reconstructed image quality from the low-mAs acquisitions, wherein the regularization plays a critical role and an established family of regularizations is based on the Markov random field (MRF) model. Inspired by the success of nonlocal means (NLM) in image processing applications, in this work, we propose to explore the NLM-based regularization for SIR to reconstruct low-dose CT images from low-mAs acquisitions. Experimental results with both digital and physical phantoms consistently demonstrated that SIR with the NLM-based regularization can achieve more gains than SIR with the well-known Gaussian MRF regularization or the generalized Gaussian MRF regularization and the conventional FBP method, in terms of image noise reduction and resolution preservation.

Three-dimensional transillumination image reconstruction for small animal with new scattering suppression technique.

To realize three-dimensional (3D) optical imaging of the internal structure of an animal body, we have developed a new technique to reconstruct optical computed tomography (optical CT) images from two-dimensional (2D) transillumination images. In transillumination imaging of an animal body using near-infrared light, the image is blurred because of the strong scattering in the tissue. To overcome this problem, we propose a novel technique to apply the point spread function (PSF) for a light source located inside the medium to the transilluminated image of light-absorbing structure. The problem of the depth-dependence of PSF was solved in the calculation of the projection image in the filtered back-projection method. The effectiveness of the proposed technique was assessed in the experiments with a model phantom and a mouse. These analyses verified the feasibility of the practical 3D imaging of the internal light-absorbing structure of a small animal.

Deriving adaptive MRF coefficients from previous normal‐dose CT scan for low‐dose image reconstruction via penalized weighted least‐squares minimization

Repeated computed tomography (CT) scans are required for some clinical applications such as image-guided interventions. To optimize radiation dose utility, a normal-dose scan is often first performed to set up reference, followed by a series of low-dose scans for intervention. One common strategy to achieve the low-dose scan is to lower the x-ray tube current and exposure time (mAs) or tube voltage (kVp) setting in the scanning protocol, but the resulted image quality by the conventional filtered back-projection (FBP) method may be severely degraded due to the excessive noise. Penalized weighted least-squares (PWLS) image reconstruction has shown the potential to significantly improve the image quality from low-mAs acquisitions, where the penalty plays an important role. In this work, the authors' explore an adaptive Markov random field (MRF)-based penalty term by utilizing previous normal-dose scan to improve the subsequent low-dose scans image reconstruction. In this work, the authors employ the widely-used quadratic-form MRF as the penalty model and explore a novel idea of using the previous normal-dose scan to obtain the MRF coefficients for adaptive reconstruction of the low-dose images. In the coefficients determination, the authors further explore another novel idea of using the normal-dose scan to obtain a scale map, which describes an optimal neighborhood for the coefficients determination such that a local uniform region has a small spread of frequency spectrum and, therefore, a small MRF window, and vice versa. The proposed penalty term is incorporated into the PWLS image reconstruction framework, and the low-dose images are reconstructed via the PWLS minimization. The presented adaptive MRF based PWLS algorithm was validated by physical phantom and patient data. The experimental results demonstrated that the presented algorithm is superior to the PWLS reconstruction using the conventional Gaussian MRF penalty or the edge-preserving Huber penalty and the conventional FBP method, in terms of image noise reduction and edge/detail/contrast preservation. This study demonstrated the feasibility and efficacy of the proposed scheme in utilizing previous normal-dose CT scan to improve the subsequent low-dose scans.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo(®), GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a "redder" NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose)(-β) with the component β ≈ 0.25, which violated the classical σ ∝ (dose)(-0.5) power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image generated from two MBIR images acquired at two different dose levels (D1 and D2) demonstrated lower noise than that of an image acquired at a dose level of D1+D2. The noise characteristics of the MBIR method are significantly different from those of the FBP method. The well known tradeoff relationship between CT image noise and radiation dose has been modified by MBIR to establish a more gradual dependence of noise on dose. Additionally, some other CT noise properties that had been well understood based on the linear system theory have also been altered by MBIR. Clinical CT scan protocols that had been optimized based on the classical CT noise properties need to be carefully re-evaluated for systems equipped with MBIR in order to maximize the method's potential clinical benefits in dose reduction and/or in CT image quality improvement.