Standard Filtered Backprojection Algorithm Research Articles

Directional TV algorithm for fast EPR imaging

Precise radiation guided by oxygen images has demonstrated superiority over the traditional radiation methods. Electron paramagnetic resonance (EPR) imaging has proven to be the most advanced oxygen imaging modality. However, the main drawback of EPR imaging is the long scan time. For each projection, we usually need to collect the projection many times and then average them to achieve high signal-to-noise ratio (SNR). One approach to fast scan is to reduce the repeating time for each projection. While the projections would be noisy and thus the traditional commonly-use filtered backprojection (FBP) algorithm would not be capable of accurately reconstructing images. Optimization-based iterative algorithms may accurately reconstruct images from noisy projections for they may incorporate prior information into optimization models. Based on the total variation (TV) algorithms for EPR imaging, in this work, we propose a directional TV (DTV) algorithm to further improve the reconstruction accuracy. We construct the DTV constrained, data divergence minimization (DTVcDM) model, derive its Chambolle–Pock (CP) solving algorithm, validate the correctness of the whole algorithm, and perform evaluations via simulated and real data. The experimental results show that the DTV algorithm outperforms the existing TV and FBP algorithms in fast EPR imaging. Compared to the standard FBP algorithm, the proposed algorithm may achieve 10 times of acceleration.

Effect of Different Iterative Reconstruction Algorithms on Ultra-Low Dose CT of Inflammatory Bowel Disease in a Rabbit Model

Purpose: To evaluate the feasibility of ultra-low dose 80 kVp CT for the evaluation of inflammatory bowel disease (IBD) in a rabbit model and to investigate the effect of two different iterative reconstruction (IR) algorithms on 80 kVp CT in terms of image quality and diagnostic performance in comparison with same session conventional 120 kVp images.Materials and Methods: This study was approved by the Animal Care and Use Committee of our hospital. Twenty-eight New Zealand white rabbits were randomly divided into two groups: IBD group (n=18) and a control group (n=10). To create an acute IBD model, 3mL of a 5% w/v tri-nitrobenzene sulfonic acid solution was administered to the sigmoid colon of the rabbits. CT was performed at 80 kVp and 120 kVp and was reconstructed using filtered back projection (FBP), hybrid statistic-based IR, and full IR algorithms for 80 kVp and using FBP only for 120 kVp. Effective radiation dose, image noise, image quality, and diagnostic performance by two reviewers were recorded and compared using repeated measure analysis of variance, McNemar test, and receiver operating curve (ROC) analysis.Results: Mean effective radiation dose of 80 kVp CT (0.05 mSv) was significantly lower than that (0.285 mSv) of 120 kVp CT. Mean image noise was highest in the 80 kVp FBP setting (60.36) but significantly decreased with IR algorithms (47.02 with hybrid IR and 12.92 with full IR) (P<0.0001). Mean overall image quality score was lowest in the 80 kVp FBP setting (1.57 and 1.46 for reviewers 1 and 2, respectively) but significantly improved with IR algorithms (2.43 and 2.25 for hybrid IR and 4.79 and 4.93 for full IR) (P<0.0001). Sensitivity and area under the curve (AUC) for differentiating a normal bowel from IBD was lowest with 80 kVp FBP (61.1% and 83.3%; 0.883 and 0.967) but improved with IR algorithms (83.3%~100%; 0.992~1), to similar levels as the 120 kVp FBP setting (100% and 1). Differences in sensitivity and AUC between 80 kVp FBP and 80 kVp IR algorithms were statistically significant in reviewer 1.Conclusions: Ultra-low dose 80 kVp CT in a rabbit IBD model is not feasible using the standard FBP algorithm. However, with the application of IR algorithms, diagnostic performance of 80 kVp CT was acceptable and on par with that at conventional 120 kVp FBP.

Analytic Computed Tomography Reconstruction in Sparse-Angular Sampling Using a Sinogram-Normalization Interpolation Method

This study investigated analytic computed tomography (CT) reconstruction in sparse-angular sampling using a new sinogram interpolation method to reduce patient radiation dosage. In sparse-angle CT, only a small number of projections, far less than what is required by the Nyquist sampling theory, are taken from the CT system and used for image reconstruction. However, CT images reconstructed by using the standard filtered-backprojection algorithm usually suffer from severe streak artifacts due to theoretically insufficient angular sampling. In this study, a new sinogram interpolation method, the so-called sinogram-normalization interpolation, was introduced to the analytic sparse-angle CT reconstruction to alleviate such artifacts. To validate the proposed method, we performed a systematic simulation and experiment and investigated the image characteristics. CT images were reconstructed using the three sparse-angular samplings of 100, 120, and 150, and their image qualities were quantitatively evaluated in terms of the intensity profile, the peak signal-tonoise ratio, and the universal quality index. The results indicated that the proposed interpolation method effectively reduced streak artifacts in the analytic sparse-angle CT reconstruction, thus maintaining the image quality.

One-mSv CT colonography: Effect of different iterative reconstruction algorithms on radiologists’ performance

PurposeTo analyze the effect of different reconstruction algorithms on image noise and radiologists’ performance at ultra-low dose CT colonography (CTC) in human subjects. Materials and methodsThis retrospective study had institutional review board approval, with waiver of the need to obtain informed consent. CTC and subsequent colonoscopy were performed at the same day in 28 patients. CTC was scanned at the supine/prone positions using 120/100kVp and fixed 10mAs, and reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based IR (Veo) algorithms. Size-specific dose estimates (SSDE) and effective radiation doses were recorded. Image noise was compared among the three datasets using repeated measures analysis of variance (ANOVA). Per-polyp sensitivity and figure-of-merits were compared among the datasets using the McNemar test and jackknife alternative free-response receiver operating characteristic (JAFROC) analysis, respectively, by one novice and one expert reviewer in CTC. ResultsMean SSDE and effective radiation dose of CTC were 1.732mGy and 1.002mSv, respectively. Mean image noise at supine/prone position datasets was significantly lowest with Veo (17.2/13.3), followed by ASIR (52.4/38.9) and FBP (69.9/50.8) (P<0.0001). Forty-two polyps in 25 patients were reference polyps. For both readers, per-polyp sensitivity of all 42 polyps was highest with Veo reconstruction (81.0%, 64.3%), followed by ASIR (73.8%, 54.8%) and FBP (57.1%, 50.0%) with statistical significance between Veo and FBP for reader 1 (P=0.002). JAFROC analysis revealed that the figure-of-merit for the detection of polyps was highest with Veo (0.917, 0.786), followed by ASIR (0.881, 0.750) and FBP (0.750, 0.746) with statistical significances between Veo or ASIR and FBP for reader 1 (P<0.05). ConclusionOne-mSv CTC was not feasible using the standard FBP algorithm. However, diagnostic performance expressed as per-polyp sensitivity and figures-of-merit can be improved with the application of IR algorithms, particularly Veo.

An iterative deconvolution algorithm for image recovery in clinical CT: A phantom study

PurposeTo study the feasibility of using an iterative reconstruction algorithm to improve previously reconstructed CT images which are judged to be non-diagnostic on clinical review. A novel rapidly converging, iterative algorithm (RSEMD) to reduce noise as compared with standard filtered back-projection algorithm has been developed. Materials and methodsThe RSEMD method was tested on in-silico, Catphan®500, and anthropomorphic 4D XCAT phantoms. The method was applied to noisy CT images previously reconstructed with FBP to determine improvements in SNR and CNR. To test the potential improvement in clinically relevant CT images, 4D XCAT phantom images were used to simulate a small, low contrast lesion placed in the liver. ResultsIn all of the phantom studies the images proved to have higher resolution and lower noise as compared with images reconstructed by conventional FBP. In general, the values of SNR and CNR reached a plateau at around 20 iterations with an improvement factor of about 1.5 for in noisy CT images. Improvements in lesion conspicuity after the application of RSEMD have also been demonstrated. The results obtained with the RSEMD method are in agreement with other iterative algorithms employed either in image space or with hybrid reconstruction algorithms. ConclusionsIn this proof of concept work, a rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach that operates on DICOM CT images has been demonstrated. The RSEMD method can be applied to sub-optimal routine-dose clinical CT images to improve image quality to potentially diagnostically acceptable levels.

Geometric correction method for 3D in-line X-ray phase contrast image reconstruction.

BackgroundMechanical system with imperfect or misalignment of X-ray phase contrast imaging (XPCI) components causes projection data misplaced, and thus result in the reconstructed slice images of computed tomography (CT) blurred or with edge artifacts. So the features of biological microstructures to be investigated are destroyed unexpectedly, and the spatial resolution of XPCI image is decreased. It makes data correction an essential pre-processing step for CT reconstruction of XPCI.MethodsTo remove unexpected blurs and edge artifacts, a mathematics model for in-line XPCI is built by considering primary geometric parameters which include a rotation angle and a shift variant in this paper. Optimal geometric parameters are achieved by finding the solution of a maximization problem. And an iterative approach is employed to solve the maximization problem by using a two-step scheme which includes performing a composite geometric transformation and then following a linear regression process. After applying the geometric transformation with optimal parameters to projection data, standard filtered back-projection algorithm is used to reconstruct CT slice images.ResultsNumerical experiments were carried out on both synthetic and real in-line XPCI datasets. Experimental results demonstrate that the proposed method improves CT image quality by removing both blurring and edge artifacts at the same time compared to existing correction methods.ConclusionsThe method proposed in this paper provides an effective projection data correction scheme and significantly improves the image quality by removing both blurring and edge artifacts at the same time for in-line XPCI. It is easy to implement and can also be extended to other XPCI techniques.

Clinical impact of an adaptive statistical iterative reconstruction algorithm for detection of hypervascular liver tumours using a low tube voltage, high tube current MDCT technique

To investigate the impact of an adaptive statistical iterative reconstruction (ASiR) algorithm on diagnostic accuracy and confidence for the diagnosis of hypervascular liver tumours, as well as the reader's perception of image quality, using a low tube voltage (80 kVp), high tube current computed tomography (CT) technique. Forty patients (29 men, 11 women) with 65 hypervascular liver tumours underwent dual energy CT. The 80 kV set of the dual energy acquisition was reconstructed with standard filtered backprojection (FBP) and ASiR at different blending levels. Lesion contrast-to-noise ratio (CNR), reader's confidence for lesion detection and characterisation, and reader's evaluation of image quality were recorded. ASiR yielded significantly higher CNR values compared with FBP (P < 0.0001 for all comparisons). Reader's perception of lesion conspicuity and confidence in the diagnosis of malignancy were also higher with 60 % and 80 % ASiR, compared with FBP (P = 0.01 and < 0.001, respectively). Compared with FBP, ASiR yielded nearly significantly lower specificity for lesion detection and a substantial decrease in the reader's perception of image quality. Compared with the standard FBP algorithm, ASiR significantly improves conspicuity of hypervascular liver lesions. This improvement may come at the cost of decreased specificity and reader's perception of image quality.

Rational approximations for tomographic reconstructions

We use optimal rational approximations of projection data collected in x-ray tomography to improve image resolution. Under the assumption that the object of interest is described by functions with jump discontinuities, for each projection we construct its rational approximation with a small (near optimal) number of terms for a given accuracy threshold. This allows us to augment the measured data, i.e., double the number of available samples in each projection or, equivalently, extend (double) the domain of their Fourier transform. We also develop a new, fast, polar coordinate Fourier domain algorithm which uses our nonlinear approximation of projection data in a natural way. Using augmented projections of the Shepp–Logan phantom, we provide a comparison between the new algorithm and the standard filtered back-projection algorithm. We demonstrate that the reconstructed image has improved resolution without additional artifacts near sharp transitions in the image.

Vascular Diameter Measurement in CT Angiography: Comparison of Model-Based Iterative Reconstruction and Standard Filtered Back Projection Algorithms In Vitro

The purpose of this study was to evaluate the performance of model-based iterative reconstruction (MBIR) in measurement of the inner diameter of models of blood vessels and compare performance between MBIR and a standard filtered back projection (FBP) algorithm. Vascular models with wall thicknesses of 0.5, 1.0, and 1.5 mm were scanned with a 64-MDCT unit and densities of contrast material yielding 275, 396, and 542 HU. Images were reconstructed images by MBIR and FBP, and the mean diameter of each model vessel was measured by software automation. Twenty separate measurements were repeated for each vessel, and variance among the repeated measures was analyzed for determination of measurement error. For all nine model vessels, CT attenuation profiles were compared along a line passing through the luminal center on axial images reconstructed with FBP and MBIR, and the 10-90% edge rise distances at the boundary between the vascular wall and the lumen were evaluated. For images reconstructed with FBP, measurement errors were smallest for models with 1.5-mm wall thickness, except those filled with 275-HU contrast material, and errors grew as the density of the contrast material decreased. Measurement errors with MBIR were comparable to or less than those with FBP. In CT attenuation profiles of images reconstructed with MBIR, the 10-90% edge rise distances at the boundary between the lumen and vascular wall were relatively short for each vascular model compared with those of the profile curves of FBP images. MBIR is better than standard FBP for reducing reconstruction blur and improving the accuracy of diameter measurement at CT angiography.

Noise-reducing algorithms do not necessarily provide superior dose optimisation for hepatic lesion detection with multidetector CT

To compare the dose-optimisation potential of a smoothing filtered backprojection (FBP) and a hybrid FBP/iterative algorithm to that of a standard FBP algorithm at three slice thicknesses for hepatic lesion detection with multidetector CT. A liver phantom containing a 9.5-mm opacity with a density of 10 HU below background was scanned at 125, 100, 75, 50 and 25 mAs. Data were reconstructed with standard FBP (B), smoothing FBP (A) and hybrid FBP/iterative (iDose(4)) algorithms at 5-, 3- and 1-mm collimation. 10 observers marked opacities using a four-point confidence scale. Jackknife alternative free-response receiver operating characteristic figure of merit (FOM), sensitivity and noise were calculated. Compared with the 125-mAs/5-mm setting for each algorithm, significant reductions in FOM (p<0.05) and sensitivity (p<0.05) were found for all three algorithms for all exposures at 1-mm thickness and for all slice thicknesses at 25 mAs, with the exception of the 25-mAs/5-mm setting for the B algorithm. Sensitivity was also significantly reduced for all exposures at 3-mm thickness for the A algorithm (p<0.05). Noise for the A and iDose(4) algorithms was approximately 13% and 21% lower, respectively, than for the B algorithm. Superior performance for hepatic lesion detection was not shown with either a smoothing FBP algorithm or a hybrid FBP/iterative algorithm compared with a standard FBP technique, even though noise reduction with thinner slices was demonstrated with the alternative approaches. Reductions in image noise with non-standard CT algorithms do not necessarily translate to an improvement in low-contrast object detection.

Improved Image Quality in Dual-Energy Abdominal CT: Comparison of Iterative Reconstruction in Image Space and Filtered Back Projection Reconstruction

The purpose of this study is to investigate whether an iterative reconstruction in image space (IRIS) algorithm improves the image quality of dual-energy CT abdominal examinations performed during the hepatic arterial phase. Seventy patients with suspected liver masses underwent contrast-enhanced multiphase abdominal examination and were enrolled in the study. A dual-energy CT protocol was performed in the hepatic arterial phase (parameters: tube A, 140 kV and 90 mA; tube B, 80 kV and 382 mA; automatic tube current modulation on; and collimation, 14 × 1.2 mm). The reconstructions were performed with filtered back projection (FBP) and IRIS algorithms at a slice thickness of 3 mm and kernels of B30 and I30. The image noise was measured on the liver, aorta, and subcutaneous fat on the FBP and IRIS fusion images (m = 0.3) at the same position. The image noise and diagnostic acceptability of all images were scored by two radiologists. The image noise using the IRIS algorithm was lower than that using the standard FBP algorithm on the liver, aorta, and subcutaneous fat, respectively. The signal-to-noise ratio and contrast-to-noise ratio of images reconstructed with the IRIS algorithm also were significantly higher than for those reconstructed with the FBP algorithm. The diagnostic acceptability score using the IRIS algorithm was higher than that using the FBP algorithm at the same dose level (1.20 ± 0.40 vs 1.37 ± 0.57; p < 0.05). Compared with standard FBP reconstruction, an IRIS algorithm enables significant reduction of image noise and improvement of image quality and has the potential to decrease radiation exposure during contrast-enhanced dual-energy CT abdominal examination.

Measurement of vascular wall attenuation: Comparison of CT angiography using model-based iterative reconstruction with standard filtered back-projection algorithm CT in vitro

ObjectivesTo compare the performance of model-based iterative reconstruction (MBIR) with that of standard filtered back projection (FBP) for measuring vascular wall attenuation. Study designAfter subjecting 9 vascular models (actual attenuation value of wall, 89HU) with wall thickness of 0.5, 1.0, or 1.5mm that we filled with contrast material of 275, 396, or 542HU to scanning using 64-detector computed tomography (CT), we reconstructed images using MBIR and FBP (Bone, Detail kernels) and measured wall attenuation at the center of the wall for each model. We performed attenuation measurements for each model and additional supportive measurements by a differentiation curve. We analyzed statistics using analyzes of variance with repeated measures. ResultsUsing the Bone kernel, standard deviation of the measurement exceeded 30HU in most conditions. In measurements at the wall center, the attenuation values obtained using MBIR were comparable to or significantly closer to the actual wall attenuation than those acquired using Detail kernel. Using differentiation curves, we could measure attenuation for models with walls of 1.0- or 1.5-mm thickness using MBIR but only those of 1.5-mm thickness using Detail kernel. We detected no significant differences among the attenuation values of the vascular walls of either thickness (MBIR, P=0.1606) or among the 3 densities of intravascular contrast material (MBIR, P=0.8185; Detail kernel, P=0.0802). ConclusionsCompared with FBP, MBIR reduces both reconstruction blur and image noise simultaneously, facilitates recognition of vascular wall boundaries, and can improve accuracy in measuring wall attenuation.

Low‐dose 4DCT reconstruction via temporal nonlocal means

Four-dimensional computed tomography (4DCT) has been widely used in cancer radiotherapy for accurate target delineation and motion measurement for tumors in the thorax and upper abdomen areas. However, its prolonged scanning duration causes a considerable increase of radiation dose compared to conventional CT, which is a major concern in its clinical application. This work is to develop a new algorithm to reconstruct 4DCT images from undersampled projections acquired at low mA s levels in order to reduce the imaging dose. Conventionally, each phase of 4DCT is reconstructed independently using the filtered backprojection (FBP) algorithm. The basic idea of the authors' new algorithm is that by utilizing the common information among different phases, the input information required to reconstruct the image of high quality, and thus the imaging dose, can be reduced. The authors proposed a temporal nonlocal means (TNLM) method to explore the interphase similarity. All phases of the 4DCT images are reconstructed simultaneously by minimizing a cost function consisting of a data fidelity term and a TNLM regularization term. The authors utilized a modified forward-backward splitting algorithm and a Gauss-Jacobi iteration method to efficiently solve the minimization problem. The algorithm was also implemented on a graphics processing unit (GPU) to improve the computational speed. The authors' reconstruction algorithm has been tested on a digital NCAT thorax phantom in three low dose scenarios: All projections with low mA s level, undersampled projections with high mA s level, and undersampled projections with low mA s level. In all three low dose scenarios, the new algorithm generates visually much better CT images containing less image noise and streaking artifacts compared to the standard FBP algorithm. Quantitative analysis shows that by comparing the authors' TNLM algorithm to the standard FBP algorithm, the contrast-to-noise ratio has been improved by a factor of 3.9-10.2 and the signal-to-noise ratio has been improved by a factor of 2.1-5.9, depending on the cases. In the situation of undersampled projection data, the majority of the streaks in the images reconstructed by FBP can be suppressed using the authors' algorithm. The total reconstruction time for all ten phases of a slice ranges from 40 to 90 s on an NVIDIA Tesla C1060 GPU card. The experimental results indicate that the authors' new algorithm outperforms the conventional FBP algorithm in effectively reducing the image artifacts due to undersampling and suppressing the image noise due to the low mA s level.

Prior image constrained scatter correction in cone-beam computed tomography image-guided radiation therapy

X-ray scatter is a significant problem in cone-beam computed tomography when thicker objects and larger cone angles are used, as scattered radiation can lead to reduced contrast and CT number inaccuracy. Advances have been made in x-ray computed tomography (CT) by incorporating a high quality prior image into the image reconstruction process. In this paper, we extend this idea to correct scatter-induced shading artifacts in cone-beam CT image-guided radiation therapy. Specifically, this paper presents a new scatter correction algorithm which uses a prior image with low scatter artifacts to reduce shading artifacts in cone-beam CT images acquired under conditions of high scatter. The proposed correction algorithm begins with an empirical hypothesis that the target image can be written as a weighted summation of a series of basis images that are generated by raising the raw cone-beam projection data to different powers, and then, reconstructing using the standard filtered backprojection algorithm. The weight for each basis image is calculated by minimizing the difference between the target image and the prior image. The performance of the scatter correction algorithm is qualitatively and quantitatively evaluated through phantom studies using a Varian 2100 EX System with an on-board imager. Results show that the proposed scatter correction algorithm using a prior image with low scatter artifacts can substantially mitigate scatter-induced shading artifacts in both full-fan and half-fan modes.

Bronnikov-aided correction for x-ray computed tomography

When a very-low-absorbing sample is scanned at an x-ray computed tomography setup with a microfocus x-ray tube and a high-resolution detector, the obtained projection images contain not only absorption contrast but also phase contrast. While images without a phase signal can be reconstructed very well, such mixed phase and absorption images give rise to severe artifacts in the reconstructed slices. A method is described that applies a correction to these mixed projections to remove the phase signal. These corrected images can then be processed using a standard filtered backprojection algorithm to obtain reconstructions with only few or no phase artifacts. This new method, which we call the Bronnikov-aided correction (BAC), can be used in a broad variety of applications and without much additional effort. It is tested on a biological and a pharmaceutical sample, and results are evaluated and discussed by comparing them with those of conventional reconstruction methods.

WE-D-332-08: Experimental Demonstration of Simultaneous High Spatial and High Temporal Resolution Using Prior Image Constrained Compressed Sensing (PICCS) for Gated CT Reconstruction

Purpose: Recently an extension to compressed sensing theory has been proposed in which a prior image is used to constrain the reconstruction process. This new algorithm may be applied to gated CT acquisitions where a fully sampled ‘blurred’ image is used as the prior image to constrain imagesreconstructed at each phase. Our hypothesis is that the PICCS algorithm can accurately track moving objects throughout a given cyclic motion profile. The purpose of this study is to experimentally verify this hypothesis. Method and Materials: The PICCS algorithm was implemented on a clinical C‐arm system (GE Innova 4100). A phantom was constructed using human bones to simulate a realistic background of ribs and vertebrae. A 3 mm plastic rod was scanned along a one dimensional motion profile. The motion profile had a period of 0.8sec with a resting phase of 0.2 sec, and an amplitude of 8 mm. 420 cone‐beam projections were acquired using a 14 second data acquisition time over 210 degrees. PICCS reconstructed was applied to the gated data such that 25 phases were reconstructed.Results: The center of mass of the moving rod was calculated based on the reconstructed images and agrees well with the programmed motion profile for all points in the simulated motion profile. Intensity plots are given comparing the gated PICCS reconstruction to the standard filtered backprojection algorithm. The PICCS reconstruction results also faithfully depict the width of the moving objects. When the width of the gating window in the PICCS algorithm is increased the width of the reconstructed moving object increases. Conclusion: This study demonstrates that for moving objects PICCS has the ability to reconstructimages with simultaneous high spatial resolution and temporal resolution via gated reconstruction. PICCS has the potential to improve reconstruction for gated acquisitions such as cardiac and lungimaging.

An RPC-PET prototype with high spatial resolution

A small positron emission tomography system, based on the timing RPC technology has been built and tested. This first prototype is aimed at validating the expectations, derived from simulations, of a very high spatial resolution, which could be of value for the imaging of small animals. The system is composed of two counting heads, able to measure the photon interaction point in two dimensions, the transaxial dimension and the Depth of Interaction. Each head is composed of 16 independent stacked RPCs made from copper and glass (anode) electrodes. Point-like 22Na sources were so far reconstructed, using the standard filtered back-projection algorithm, with a spatial accuracy of 0.6mm FWHM, free of parallax error.

Breast tomography with synchrotron radiation: preliminary results**This work is dedicated to the memory of Paolo Poropat, who died tragically on June 8th, 2002. He was a brilliant experimental scientist and gave relevant contributions to the fields of high energy physics and medical physics. He had a very rich and versatile personality, a brilliant character, a big vitality. We will never

A system for in vivo breast imaging with monochromatic x-rays has been designed and built at the synchrotron radiation facility Elettra in Trieste (Italy) and will be operational in 2004. The system design involves the possibility of performing both planar mammography and breast tomography. In the present work, the first results obtained with a test set-up for breast tomography are shown and discussed. Tomographic images of in vitro breasts were acquired using monochromatic x-ray beams in the energy range 20–28 keV and a linear array silicon pixel detector. Tomograms were reconstructed using standard filtered backprojection algorithms; the effect of different filters was evaluated. The attenuation coefficients of fibroglandular and adipose tissue were measured, and a quantitative comparison of images acquired at different energies was performed by calculating the differential signal-to-noise ratio of fibroglandular details in adipose tissue. All images required a dose comparable to the dose delivered in clinical, conventional mammography and showed a high resolution of the breast structures without the overlapping effects that limit the visibility of the structures in 2D mammography. A quantitative evaluation of the images proves that the image quality at a given dose increases in the considered energy range and for the considered breast sizes.

37. Evaluation of pinhole SPECT using a standard filtered back-projection algorithm

37. Evaluation of pinhole SPECT using a standard filtered back-projection algorithm

Differences due to collimator blurring in cardiac images with use of circular and elliptic camera orbits

Background. In cardiac imaging systems, an elliptic acquisition orbit about the patient can be used to enhance resolution of single photon emission computed tomography (SPECT) images by minimizing the distance between the object imaged and the rotating detector system. In this study artifacts from images acquired with the standard circular acquisition are compared with those acquired with various elliptic acquisitions. Methods and Results. With the use of elliptic camera orbits of different eccentricities, simulated projection data were generated from a slice through the left ventricle (LV). The projection data included a simulation of the degradation due to the depth-dependent response of the collimator. As is common in many clinical systems, SPECT images were reconstructed with the standard filtered backprojection algorithm without correction for the collimator response. When the ratio of the major-to-minor axis of the acquisition arc is changed from 1 (circular) to 1.5 (elliptic), reconstructed SPECT images show an additional loss of counts (about 10%) in the apical region of the LV. The severity of the apical defect is also dependent on the starting angle of the acquisition arc. When the starting angle is changed from 0° (detector parallel to the major axis of the LV) to 60°, the ratio between the minimum count in the apical region and the maximum count in the left ventricular myocardial wall decreases by as much as 20%. Conclusions. SPECT image artifacts from elliptic acquisitions are significantly more severe than those from circular acquisitions. Because of the significant difference in images reconstructed from circular and elliptic acquisitions, standardized normal files acquired from circular acquisitions should not be used for comparisons with patient data acquired from elliptic acquisitions. (J Nucl Cardiol 2001;8:458-65.)