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Sample records for 3-dimensional reconstruction ct

  1. Mandibular reconstruction using stereolithographic 3-dimensional printing modeling technology.

    PubMed

    Cohen, Adir; Laviv, Amir; Berman, Phillip; Nashef, Rizan; Abu-Tair, Jawad

    2009-11-01

    Mandibular reconstruction can be challenging for the surgeon wishing to restore its unique geometry. Reconstruction can be achieved with titanium bone plates followed by autogenous bone grafting. Incorporation of the bone graft into the mandible provides continuity and strength required for proper esthetics and function and permitting dental implant rehabilitation at a later stage. Precious time in the operating room is invested in plate contouring to reconstruct the mandible. Rapid prototyping technologies can construct physical models from computer-aided design via 3-dimensional (3D) printers. A prefabricated 3D model is achieved, which assists in accurate contouring of plates and/or planning of bone graft harvest geometry before surgery. The 2 most commonly used rapid prototyping technologies are stereolithography and 3D printing (3DP). Three-dimensional printing is advantageous to stereolithography for better accuracy, quicker printing time, and lower cost. We present 3 clinical cases based on 3DP modeling technology. Models were fabricated before the resection of mandibular ameloblastoma and were used to prepare bridging plates before the first stage of reconstruction. In 1 case, another model was fabricated and used as a template for iliac crest bone graft in the second stage of reconstruction. The 3DP technology provided a precise, fast, and cheap mandibular reconstruction, which aids in shortened operation time (and therefore decreased exposure time to general anesthesia, decreased blood loss, and shorter wound exposure time) and easier surgical procedure.

  2. DETECTORS AND EXPERIMENTAL METHODS: Decay vertex reconstruction and 3-dimensional lifetime determination at BESIII

    NASA Astrophysics Data System (ADS)

    Xu, Min; He, Kang-Lin; Zhang, Zi-Ping; Wang, Yi-Fang; Bian, Jian-Ming; Cao, Guo-Fu; Cao, Xue-Xiang; Chen, Shen-Jian; Deng, Zi-Yan; Fu, Cheng-Dong; Gao, Yuan-Ning; Han, Lei; Han, Shao-Qing; He, Miao; Hu, Ji-Feng; Hu, Xiao-Wei; Huang, Bin; Huang, Xing-Tao; Jia, Lu-Kui; Ji, Xiao-Bin; Li, Hai-Bo; Li, Wei-Dong; Liang, Yu-Tie; Liu, Chun-Xiu; Liu, Huai-Min; Liu, Ying; Liu, Yong; Luo, Tao; Lü, Qi-Wen; Ma, Qiu-Mei; Ma, Xiang; Mao, Ya-Jun; Mao, Ze-Pu; Mo, Xiao-Hu; Ning, Fei-Peng; Ping, Rong-Gang; Qiu, Jin-Fa; Song, Wen-Bo; Sun, Sheng-Sen; Sun, Xiao-Dong; Sun, Yong-Zhao; Tian, Hao-Lai; Wang, Ji-Ke; Wang, Liang-Liang; Wen, Shuo-Pin; Wu, Ling-Hui; Wu, Zhi; Xie, Yu-Guang; Yan, Jie; Yan, Liang; Yao, Jian; Yuan, Chang-Zheng; Yuan, Ye; Zhang, Chang-Chun; Zhang, Jian-Yong; Zhang, Lei; Zhang, Xue-Yao; Zhang, Yao; Zheng, Yang-Heng; Zhu, Yong-Sheng; Zou, Jia-Heng

    2009-06-01

    This paper focuses mainly on the vertex reconstruction of resonance particles with a relatively long lifetime such as K0S, Λ, as well as on lifetime measurements using a 3-dimensional fit. The kinematic constraints between the production and decay vertices and the decay vertex fitting algorithm based on the least squares method are both presented. Reconstruction efficiencies including experimental resolutions are discussed. The results and systematic errors are calculated based on a Monte Carlo simulation.

  3. Reconstructing a 3-dimensional image of the results of antinuclear antibody testing by indirect immunofluorescence.

    PubMed

    Murai, Ryosei; Yamada, Koji; Tanaka, Maki; Kuribayashi, Kageaki; Kobayashi, Daisuke; Tsuji, Naoki; Watanabe, Naoki

    2013-01-31

    Indirect immunofluorescence anti-nuclear antibody testing (IIF-ANAT) is an essential screening tool in the diagnosis of various autoimmune disorders. ANA titer quantification and interpretation of immunofluorescence patterns are determined subjectively, which is problematic. First, we determined the examination conditions under which IIF-ANAT fluorescence intensities are quantified. Next, IIF-ANAT was performed using homogeneous, discrete speckled, and mixed serum samples. Images were obtained using Bio Zero BZ-8000, and 3-dimensional images were reconstructed using the BZ analyzer software. In the 2-dimensional analysis, homogeneous ANAs hid the discrete speckled pattern, resulting in a diagnosis of homogeneous immunofluorescence. However, 3-dimensional analysis of the same sample showed discrete speckled-type ANA in the homogeneous background. This study strengthened the current IIF-ANAT method by providing a new approach to quantify the fluorescence intensity and enhance the resolution of IIF-ANAT fluorescence patterns. Reconstructed 3-dimensional imaging of IIF-ANAT can be a powerful tool for routine laboratory examination.

  4. Analysis of 3-dimensional finite element after reconstruction of impaired ankle deltoid ligament

    PubMed Central

    Ji, Yunhan; Tang, Xianzhong; Li, Yifan; Xu, Wei; Qiu, Wenjun

    2016-01-01

    We compared four repair techniques for impaired ankle ligament deltoideum, namely Wiltberger, Deland, Kitaoka and Hintermann using a 3-dimensional finite element. We built an ankle ligament deltoideum model, including six pieces of bone structures, gristles and main ligaments around the ankle. After testing the model, we built an impaired ligament deltoideum model plus four reconstruction models. Subsequently, different levels of force on ankles with different flexion were imposed and ankle biomechanics were compared. In the course of bending, from plantar flexion 20° to back flexion 20°, the extortion of talus decreased while the eversion increased. Four reconstruction models failed to bring back the impaired ankle to normal, with an obvious increase of extortion and eversion. The Kitaoka technique was useful to reduce the extortion angle in a consequential manner. Compared with the other three techniques, the Kitaoka technique produced better results for extortion angle and the difference was statistically significant. However, in case of eversion, there was no significant difference among the four techniques (P>0.05). Lateral ligament's stress in all the four models was different from the normal one. When the ankle was imposed with extortion moment of force, stress of anterior talofibular ligament with the Kitaoka reconstruction method was close to that of the complete deltoid ligament. When ankle was imposed with eversion moment of force, stress of anterior talofibular ligament with Kitaoka and Deland reconstruction methods were close to that of the complete deltoid ligament. We concluded that Kitaoka and Deland tendon reconstruction technique could recover impaired ankle deltoid ligament and re-established its normal biomechanics characteristics. PMID:28105122

  5. Analysis of 3-dimensional finite element after reconstruction of impaired ankle deltoid ligament.

    PubMed

    Ji, Yunhan; Tang, Xianzhong; Li, Yifan; Xu, Wei; Qiu, Wenjun

    2016-12-01

    We compared four repair techniques for impaired ankle ligament deltoideum, namely Wiltberger, Deland, Kitaoka and Hintermann using a 3-dimensional finite element. We built an ankle ligament deltoideum model, including six pieces of bone structures, gristles and main ligaments around the ankle. After testing the model, we built an impaired ligament deltoideum model plus four reconstruction models. Subsequently, different levels of force on ankles with different flexion were imposed and ankle biomechanics were compared. In the course of bending, from plantar flexion 20° to back flexion 20°, the extortion of talus decreased while the eversion increased. Four reconstruction models failed to bring back the impaired ankle to normal, with an obvious increase of extortion and eversion. The Kitaoka technique was useful to reduce the extortion angle in a consequential manner. Compared with the other three techniques, the Kitaoka technique produced better results for extortion angle and the difference was statistically significant. However, in case of eversion, there was no significant difference among the four techniques (P>0.05). Lateral ligament's stress in all the four models was different from the normal one. When the ankle was imposed with extortion moment of force, stress of anterior talofibular ligament with the Kitaoka reconstruction method was close to that of the complete deltoid ligament. When ankle was imposed with eversion moment of force, stress of anterior talofibular ligament with Kitaoka and Deland reconstruction methods were close to that of the complete deltoid ligament. We concluded that Kitaoka and Deland tendon reconstruction technique could recover impaired ankle deltoid ligament and re-established its normal biomechanics characteristics.

  6. Role of preoperative 3-dimensional computed tomography reconstruction in depressed skull fractures treated with craniectomy: a case report of forensic interest.

    PubMed

    Viel, Guido; Cecchetto, Giovanni; Manara, Renzo; Cecchetto, Attilio; Montisci, Massimo

    2011-06-01

    Patients affected by cranial trauma with depressed skull fractures and increased intracranial pressure generally undergo neurosurgical intervention. Because craniotomy and craniectomy remove skull fragments and generate new fracture lines, they complicate forensic examination and sometimes prevent a clear identification of skull fracture etiology. A 3-dimensional reconstruction based on preoperative computed tomography (CT) scans, giving a picture of the injuries before surgical intervention, can help the forensic examiner in identifying skull fracture origin and the means of production.We report the case of a 41-year-old-man presenting at the emergency department with a depressed skull fracture at the vertex and bilateral subdural hemorrhage. The patient underwent 2 neurosurgical interventions (craniotomy and craniectomy) but died after 40 days of hospitalization in an intensive care unit. At autopsy, the absence of various bone fragments did not allow us to establish if the skull had been stricken by a blunt object or had hit the ground with high kinetic energy. To analyze bone injuries before craniectomy, a 3-dimensional CT reconstruction based on preoperative scans was performed. A comparative analysis between autoptic and radiological data allowed us to differentiate surgical from traumatic injuries. Moreover, based on the shape and size of the depressed skull fracture (measured from the CT reformations), we inferred that the man had been stricken by a cylindric blunt object with a diameter of about 3 cm.

  7. A Novel Method of Orbital Floor Reconstruction Using Virtual Planning, 3-Dimensional Printing, and Autologous Bone.

    PubMed

    Vehmeijer, Maarten; van Eijnatten, Maureen; Liberton, Niels; Wolff, Jan

    2016-08-01

    Fractures of the orbital floor are often a result of traffic accidents or interpersonal violence. To date, numerous materials and methods have been used to reconstruct the orbital floor. However, simple and cost-effective 3-dimensional (3D) printing technologies for the treatment of orbital floor fractures are still sought. This study describes a simple, precise, cost-effective method of treating orbital fractures using 3D printing technologies in combination with autologous bone. Enophthalmos and diplopia developed in a 64-year-old female patient with an orbital floor fracture. A virtual 3D model of the fracture site was generated from computed tomography images of the patient. The fracture was virtually closed using spline interpolation. Furthermore, a virtual individualized mold of the defect site was created, which was manufactured using an inkjet printer. The tangible mold was subsequently used during surgery to sculpture an individualized autologous orbital floor implant. Virtual reconstruction of the orbital floor and the resulting mold enhanced the overall accuracy and efficiency of the surgical procedure. The sculptured autologous orbital floor implant showed an excellent fit in vivo. The combination of virtual planning and 3D printing offers an accurate and cost-effective treatment method for orbital floor fractures.

  8. Iterative image reconstruction in spectral CT

    NASA Astrophysics Data System (ADS)

    Hernandez, Daniel; Michel, Eric; Kim, Hye S.; Kim, Jae G.; Han, Byung H.; Cho, Min H.; Lee, Soo Y.

    2012-03-01

    Scan time of spectral-CTs is much longer than conventional CTs due to limited number of x-ray photons detectable by photon-counting detectors. However, the spectral pixel information in spectral-CT has much richer information on physiological and pathological status of the tissues than the CT-number in conventional CT, which makes the spectral- CT one of the promising future imaging modalities. One simple way to reduce the scan time in spectral-CT imaging is to reduce the number of views in the acquisition of projection data. But, this may result in poorer SNR and strong streak artifacts which can severely compromise the image quality. In this work, spectral-CT projection data were obtained from a lab-built spectral-CT consisting of a single CdTe photon counting detector, a micro-focus x-ray tube and scan mechanics. For the image reconstruction, we used two iterative image reconstruction methods, the simultaneous iterative reconstruction technique (SIRT) and the total variation minimization based on conjugate gradient method (CG-TV), along with the filtered back-projection (FBP) to compare the image quality. From the imaging of the iodine containing phantoms, we have observed that SIRT and CG-TV are superior to the FBP method in terms of SNR and streak artifacts.

  9. Can clinical CT data improve forensic reconstruction?

    PubMed

    Schuh, P; Scheurer, E; Fritz, K; Pavlic, M; Hassler, E; Rienmüller, R; Yen, K

    2013-05-01

    In accidents resulting in severe injuries, a clinical forensic examination is generally abandoned in the initial phase due to high-priority clinical needs. However, in many cases, data from clinical computed tomography (CT) examinations are available. The goals of this prospective study were (a) to evaluate clinical CT data as a basis for forensic reconstruction of the sequence of events, (b) to assess if forensic radiological follow-up reading improves the forensic diagnostic benefit compared to the written clinical radiological reports, and (c) to evaluate if full data storage including additional reconstructed 0.6-mm slices enhances forensic analysis. Clinical CT data of 15 living individuals with imaging of at least the head, thorax, and abdomen following polytrauma were examined regarding the forensic evaluation of the sequence of events. Additionally, 0.6-mm slices and 3D images were reconstructed for forensic purposes and used for the evaluation. At the forensic radiological readings, additional traumatic findings were observed in ten of the 15 patients. The main weakness of the clinical reports was that they were not detailed enough, particularly regarding the localization of injuries and description of wound morphology. In seven cases, however, forensic conclusions were possible on the basis of the written clinical reports, whereas in five cases forensic reconstruction required specific follow-up reading. The additional 0.6-mm slices were easily available and with improved 3D image quality and forensic diagnostics. In conclusion, the use of clinical CT data can considerably support forensic expertise regarding reconstruction issues. Forensic follow-up reading as well as the use of additional thin slices for 3D analysis can further improve its benefit for forensic reconstruction purposes.

  10. Fast parallel algorithm for CT image reconstruction.

    PubMed

    Flores, Liubov A; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo

    2012-01-01

    In X-ray computed tomography (CT) the X rays are used to obtain the projection data needed to generate an image of the inside of an object. The image can be generated with different techniques. Iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions and from a small number of projections. Their use may be important in portable scanners for their functionality in emergency situations. However, in practice, these methods are not widely used due to the high computational cost of their implementation. In this work we analyze iterative parallel image reconstruction with the Portable Extensive Toolkit for Scientific computation (PETSc).

  11. Optic Strut and Para-clinoid Region – Assessment by Multi-detector Computed Tomography with Multiplanar and 3 Dimensional Reconstructions

    PubMed Central

    Ravikiran, S.R.; Kumar, Ashvini; Chavadi, Channabasappa; Pulastya, Sanyal

    2015-01-01

    Purpose To evaluate thickness, location and orientation of optic strut and anterior clinoid process and variations in paraclinoid region, solely based on multidetector computed tomography (MDCT) images with multiplanar (MPR) and 3 dimensional (3D) reconstructions, among Indian population. Materials and Methods Ninety five CT scans of head and paranasal sinuses patients were retrospectively evaluated with MPR and 3D reconstructions to assess optic strut thickness, angle and location, variations like pneumatisation, carotico-clinoid foramen and inter-clinoid osseous ridge. Results Mean optic strut thickness was 3.64mm (±0.64), optic strut angle was 42.67 (±6.16) degrees. Mean width and length of anterior clinoid process were 10.65mm (±0.79) and 11.20mm (±0.95) respectively. Optic strut attachment to sphenoid body was predominantly sulcal as in 52 cases (54.74%) and was most frequently attached to anterior 2/5th of anterior clinoid process, seen in 93 sides (48.95%). Pneumatisation of optic strut occurred in 23 sides. Carotico-clinoid foramen was observed in 42 cases (22.11%), complete foramen in 10 cases (5.26%), incomplete foramen in 24 cases (12.63%) and contact type in 8 cases (4.21%). Inter-clinoid osseous bridge was seen unilaterally in 4 cases. Conclusion The study assesses morphometric features and anatomical variations of paraclinoid region using MDCT 3D and multiplanar reconstructions in Indian population. PMID:26557589

  12. 3-dimensional electron microscopic imaging of the zebrafish olfactory bulb and dense reconstruction of neurons

    PubMed Central

    Wanner, Adrian A.; Genoud, Christel; Friedrich, Rainer W.

    2016-01-01

    Large-scale reconstructions of neuronal populations are critical for structural analyses of neuronal cell types and circuits. Dense reconstructions of neurons from image data require ultrastructural resolution throughout large volumes, which can be achieved by automated volumetric electron microscopy (EM) techniques. We used serial block face scanning EM (SBEM) and conductive sample embedding to acquire an image stack from an olfactory bulb (OB) of a zebrafish larva at a voxel resolution of 9.25×9.25×25 nm3. Skeletons of 1,022 neurons, 98% of all neurons in the OB, were reconstructed by manual tracing and efficient error correction procedures. An ergonomic software package, PyKNOSSOS, was created in Python for data browsing, neuron tracing, synapse annotation, and visualization. The reconstructions allow for detailed analyses of morphology, projections and subcellular features of different neuron types. The high density of reconstructions enables geometrical and topological analyses of the OB circuitry. Image data can be accessed and viewed through the neurodata web services (http://www.neurodata.io). Raw data and reconstructions can be visualized in PyKNOSSOS. PMID:27824337

  13. Do All Patients of Breast Carcinoma Need 3-Dimensional CT-Based Planning? A Dosimetric Study Comparing Different Breast Sizes

    SciTech Connect

    Munshi, Anusheel Pai, Rajeshri H.; Phurailatpam, Reena; Budrukkar, Ashwini; Jalali, Rakesh; Sarin, Rajiv; Deshpande, D.D.; Shrivastava, Shyam K.; Dinshaw, Ketayun A.

    2009-07-01

    Evaluation of dose distribution in a single plane (i.e., 2-dimensional [2D] planning) is simple and less resource-intensive than CT-based 3-dimensional radiotherapy (3DCRT) planning or intensity modulated radiotherapy (IMRT). The aim of the study was to determine if 2D planning could be an appropriate treatment in a subgroup of breast cancer patients based on their breast size. Twenty consecutive patients who underwent breast conservation were planned for radiotherapy. The patients were grouped in 3 different categories based on their respective chest wall separation (CWS) and the thickness of breast, as 'small,' 'medium,' and 'large.' Two more contours were taken at locations 5 cm superior and 5 cm inferior to the isocenter plane. Maximum dose recorded at specified points was compared in superior/inferior slices as compared to the central slice. The mean difference for small breast size was 1.93 (standard deviation [SD] = 1.08). For medium breas size, the mean difference was 2.98 (SD = 2.40). For the large breasts, the mean difference was 4.28 (SD = 2.69). Based on our dosimetric study, breast planning only on the single isocentric contour is an appropriate technique for patients with small breasts. However, for large- and medium-size breasts, CT-based planning and 3D planning have a definite role. These results can be especially useful for rationalizing treatment in busy oncology centers.

  14. A case of pulmonary artery intimal sarcoma diagnosed with multislice CT scan with 3D reconstruction.

    PubMed

    Choi, Eui-Young; Yoon, Young-Won; Kwon, Hyuck Moon; Kim, Dongsoo; Park, Byung-Eun; Hong, Yoo-Sun; Koo, Ja-Seung; Kim, Tae-Hoon; Kim, Hyun-Seung

    2004-06-30

    Pulmonary artery intimal sarcoma is a rare highly lethal disease, with additional retrograde extension to pulmonic valve and right ventricle being an extremely rare condition. It is frequently mistaken for pulmonary thromboembolism. We report a case of 64-year-old woman with progressive dyspnea initially suspected and treated for pulmonary thromboembolism. Her helical chest CT scan with 3 dimensional (3D) reconstruction combined with echocardiography revealed a compacting main pulmonary artery mass extending to the right ventricular outflow tract and the right pulmonary artery. After excision of the mass, the patient's condition improved dramatically, and the pathologic findings revealed pulmonary intimal sarcoma. This report emphasizes that helical chest CT with 3D reconstruction can be an important tool to differentiate the characteristics of pulmonary artery lesions, such as intimal sarcoma and thromboembolism.

  15. Accelerated augmented Lagrangian method for few-view CT reconstruction

    NASA Astrophysics Data System (ADS)

    Wu, Junfeng; Mou, Xuanqin

    2012-03-01

    Recently iterative reconstruction algorithms with total variation (TV) regularization have shown its tremendous power in image reconstruction from few-view projection data, but it is much more demanding in computation. In this paper, we propose an accelerated augmented Lagrangian method (ALM) for few-view CT reconstruction with total variation regularization. Experimental phantom results demonstrate that the proposed method not only reconstruct high quality image from few-view projection data but also converge fast to the optimal solution.

  16. Analysis of shape and motion of the mitral annulus in subjects with and without cardiomyopathy by echocardiographic 3-dimensional reconstruction

    NASA Technical Reports Server (NTRS)

    Flachskampf, F. A.; Chandra, S.; Gaddipatti, A.; Levine, R. A.; Weyman, A. E.; Ameling, W.; Hanrath, P.; Thomas, J. D.

    2000-01-01

    The shape and dynamics of the mitral annulus of 10 patients without heart disease (controls), 3 patients with dilated cardiomyopathy, and 5 patients with hypertrophic obstructive cardiomyopathy and normal systolic function were analyzed by transesophageal echocardiography and 3-dimensional reconstruction. Mitral annular orifice area, apico-basal motion of the annulus, and nonplanarity were calculated over time. Annular area was largest in end diastole and smallest in end systole. Mean areas were 11.8 +/- 2.5 cm(2) (controls), 15.2 +/- 4.2 cm(2) (dilated cardiomyopathy), and 10.2 +/- 2.4 cm(2) (hypertrophic cardiomyopathy) (P = not significant). After correction for body surface, annuli from patients with normal left ventricular function were smaller than annuli from patients with dilated cardiomyopathy (5.9 +/- 1.2 cm(2)/m(2) vs 7.7 +/- 1.0 cm(2)/m(2); P <.02). The change in area during the cardiac cycle showed significant differences: 23.8% +/- 5.1% (controls), 13.2% +/- 2.3% (dilated cardiomyopathy), and 32.4% +/- 7.6% (hypertrophic cardiomyopathy) (P <.001). Apico-basal motion was highest in controls, followed by those with hypertrophic obstructive and dilated cardiomyopathy (1.0 +/- 0.3 cm, 0.8 +/- 0.2 cm, 0.3 +/- 0.2 cm, respectively; P <.01). Visual inspection and Fourier analysis showed a consistent pattern of anteroseptal and posterolateral elevations of the annulus toward the left atrium. In conclusion, although area changes and apico-basal motion of the mitral annulus strongly depend on left ventricular systolic function, nonplanarity is a structural feature preserved throughout the cardiac cycle in all three groups.

  17. Reconstructing misaligned x-ray CT data

    SciTech Connect

    Divin, C. J.

    2016-10-24

    Misalignment errors for x-ray computed tomography (CT) systems can manifest as artifacts and a loss of spatial and contrast resolution. To mitigate artifacts, significant effort is taken to determine the system geometry and minimizing any residual error in the system alignment. This project improved our ability to post-correct data which was acquired on a misaligned CT system.

  18. Limited-view Neutron CT Reconstruction with Sample Boundary

    NASA Astrophysics Data System (ADS)

    Wang, Hu; Zou, Yubin; Lu, Yuanrong; Guo, Zhiyu

    Reconstruction of limited-view CT is an ill-posed inversion problem. In order to suppress the artefacts and improve the image quality, it has been proved to be a good method toincorporatesome aprioriinformation of the sample(refers to as constraint in this paper) to the iterative process. In this paper, sample boundary is considered as a constraint and SART algorithm is chosen to test the performance of the constraint. Reconstructions from different number of projections of the famous Shepp-Logan head phantom with different levels of noise were simulated; projection data of a spark plug was acquired on the cold neutron CT platform of China Advanced Research Reactor (CARR) and the spark plug was reconstructed as well. Both the simulation and experimental results show that SART algorithm with sample boundary constraint leads to remarkable improvement of image quality and convergence speed for limited-view CT reconstruction when the noise level of projection data is less than 5%.

  19. Reconstruction 3-dimensional image from 2-dimensional image of status optical coherence tomography (OCT) for analysis of changes in retinal thickness

    SciTech Connect

    Arinilhaq,; Widita, Rena

    2014-09-30

    Optical Coherence Tomography is often used in medical image acquisition to diagnose that change due easy to use and low price. Unfortunately, this type of examination produces a two-dimensional retinal image of the point of acquisition. Therefore, this study developed a method that combines and reconstruct 2-dimensional retinal images into three-dimensional images to display volumetric macular accurately. The system is built with three main stages: data acquisition, data extraction and 3-dimensional reconstruction. At data acquisition step, Optical Coherence Tomography produced six *.jpg images of each patient were further extracted with MATLAB 2010a software into six one-dimensional arrays. The six arrays are combined into a 3-dimensional matrix using a kriging interpolation method with SURFER9 resulting 3-dimensional graphics of macula. Finally, system provides three-dimensional color graphs based on the data distribution normal macula. The reconstruction system which has been designed produces three-dimensional images with size of 481 × 481 × h (retinal thickness) pixels.

  20. Beam hardening correction for sparse-view CT reconstruction

    NASA Astrophysics Data System (ADS)

    Liu, Wenlei; Rong, Junyan; Gao, Peng; Liao, Qimei; Lu, HongBing

    2015-03-01

    Beam hardening, which is caused by spectrum polychromatism of the X-ray beam, may result in various artifacts in the reconstructed image and degrade image quality. The artifacts would be further aggravated for the sparse-view reconstruction due to insufficient sampling data. Considering the advantages of the total-variation (TV) minimization in CT reconstruction with sparse-view data, in this paper, we propose a beam hardening correction method for sparse-view CT reconstruction based on Brabant's modeling. In this correction model for beam hardening, the attenuation coefficient of each voxel at the effective energy is modeled and estimated linearly, and can be applied in an iterative framework, such as simultaneous algebraic reconstruction technique (SART). By integrating the correction model into the forward projector of the algebraic reconstruction technique (ART), the TV minimization can recover images when only a limited number of projections are available. The proposed method does not need prior information about the beam spectrum. Preliminary validation using Monte Carlo simulations indicates that the proposed method can provide better reconstructed images from sparse-view projection data, with effective suppression of artifacts caused by beam hardening. With appropriate modeling of other degrading effects such as photon scattering, the proposed framework may provide a new way for low-dose CT imaging.

  1. Quantitative image quality evaluation for cardiac CT reconstructions

    NASA Astrophysics Data System (ADS)

    Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.; Balhorn, William; Okerlund, Darin R.

    2016-03-01

    Maintaining image quality in the presence of motion is always desirable and challenging in clinical Cardiac CT imaging. Different image-reconstruction algorithms are available on current commercial CT systems that attempt to achieve this goal. It is widely accepted that image-quality assessment should be task-based and involve specific tasks, observers, and associated figures of merits. In this work, we developed an observer model that performed the task of estimating the percentage of plaque in a vessel from CT images. We compared task performance of Cardiac CT image data reconstructed using a conventional FBP reconstruction algorithm and the SnapShot Freeze (SSF) algorithm, each at default and optimal reconstruction cardiac phases. The purpose of this work is to design an approach for quantitative image-quality evaluation of temporal resolution for Cardiac CT systems. To simulate heart motion, a moving coronary type phantom synchronized with an ECG signal was used. Three different percentage plaques embedded in a 3 mm vessel phantom were imaged multiple times under motion free, 60 bpm, and 80 bpm heart rates. Static (motion free) images of this phantom were taken as reference images for image template generation. Independent ROIs from the 60 bpm and 80 bpm images were generated by vessel tracking. The observer performed estimation tasks using these ROIs. Ensemble mean square error (EMSE) was used as the figure of merit. Results suggest that the quality of SSF images is superior to the quality of FBP images in higher heart-rate scans.

  2. Iterative reconstruction methods in X-ray CT.

    PubMed

    Beister, Marcel; Kolditz, Daniel; Kalender, Willi A

    2012-04-01

    Iterative reconstruction (IR) methods have recently re-emerged in transmission x-ray computed tomography (CT). They were successfully used in the early years of CT, but given up when the amount of measured data increased because of the higher computational demands of IR compared to analytical methods. The availability of large computational capacities in normal workstations and the ongoing efforts towards lower doses in CT have changed the situation; IR has become a hot topic for all major vendors of clinical CT systems in the past 5 years. This review strives to provide information on IR methods and aims at interested physicists and physicians already active in the field of CT. We give an overview on the terminology used and an introduction to the most important algorithmic concepts including references for further reading. As a practical example, details on a model-based iterative reconstruction algorithm implemented on a modern graphics adapter (GPU) are presented, followed by application examples for several dedicated CT scanners in order to demonstrate the performance and potential of iterative reconstruction methods. Finally, some general thoughts regarding the advantages and disadvantages of IR methods as well as open points for research in this field are discussed.

  3. Limited view CT reconstruction and segmentation via constrained metric labeling

    PubMed Central

    Singh, Vikas; Mukherjee, Lopamudra; Dinu, Petru M.; Xu, Jinhui; Hoffmann, Kenneth R.

    2008-01-01

    This paper proposes a new discrete optimization framework for tomographic reconstruction and segmentation of CT volumes when only a few projection views are available. The problem has important clinical applications in coronary angiographic imaging. We first show that the limited view reconstruction and segmentation problem can be formulated as a “constrained” version of the metric labeling problem. This lays the groundwork for a linear programming framework that brings metric labeling classification and classical algebraic tomographic reconstruction (ART) together in a unified model. If the imaged volume is known to be comprised of a finite set of attenuation coefficients (a realistic assumption), given a regular limited view reconstruction, we view it as a task of voxels reassignment subject to maximally maintaining consistency with the input reconstruction and the objective of ART simultaneously. The approach can reliably reconstruct (or segment) volumes with several multiple contrast objects. We present evaluations using experiments on cone beam computed tomography. PMID:19802346

  4. CT reconstruction via denoising approximate message passing

    NASA Astrophysics Data System (ADS)

    Perelli, Alessandro; Lexa, Michael A.; Can, Ali; Davies, Mike E.

    2016-05-01

    In this paper, we adapt and apply a compressed sensing based reconstruction algorithm to the problem of computed tomography reconstruction for luggage inspection. Specifically, we propose a variant of the denoising generalized approximate message passing (D-GAMP) algorithm and compare its performance to the performance of traditional filtered back projection and to a penalized weighted least squares (PWLS) based reconstruction method. D-GAMP is an iterative algorithm that at each iteration estimates the conditional probability of the image given the measurements and employs a non-linear "denoising" function which implicitly imposes an image prior. Results on real baggage show that D-GAMP is well-suited to limited-view acquisitions.

  5. Tensor decomposition and nonlocal means based spectral CT reconstruction

    NASA Astrophysics Data System (ADS)

    Zhang, Yanbo; Yu, Hengyong

    2016-10-01

    As one of the state-of-the-art detectors, photon counting detector is used in spectral CT to classify the received photons into several energy channels and generate multichannel projection simultaneously. However, the projection always contains severe noise due to the low counts in each energy channel. How to reconstruct high-quality images from photon counting detector based spectral CT is a challenging problem. It is widely accepted that there exists self-similarity over the spatial domain in a CT image. Moreover, because a multichannel CT image is obtained from the same object at different energy, images among channels are highly correlated. Motivated by these two characteristics of the spectral CT, we employ tensor decomposition and nonlocal means methods for spectral CT iterative reconstruction. Our method includes three basic steps. First, each channel image is updated by using the OS-SART. Second, small 3D volumetric patches (tensor) are extracted from the multichannel image, and higher-order singular value decomposition (HOSVD) is performed on each tensor, which can help to enhance the spatial sparsity and spectral correlation. Third, in order to employ the self-similarity in CT images, similar patches are grouped to reduce noise using the nonlocal means method. These three steps are repeated alternatively till the stopping criteria are met. The effectiveness of the developed algorithm is validated on both numerically simulated and realistic preclinical datasets. Our results show that the proposed method achieves promising performance in terms of noise reduction and fine structures preservation.

  6. Parametric boundary reconstruction algorithm for industrial CT metrology application.

    PubMed

    Yin, Zhye; Khare, Kedar; De Man, Bruno

    2009-01-01

    High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly

  7. Reconstruction filters and contrast detail curves in CT

    NASA Astrophysics Data System (ADS)

    Huda, W.; Ogden, K. M.; Samei, E.; Scalzetti, E. M.; Lavallee, R. L.; Roskopf, M. L.; Groat, G. E.

    2008-03-01

    In this study, we investigated the effect of CT reconstruction filters in abdominal CT images of a male anthropomorphic phantom. A GE Light Speed CT 4-slice scanner was used to scan the abdomen of an adult Rando phantom. Cross sectional images of the phantom were reconstructed using four reconstruction filters: (1) soft tissue with the lowest noise; (2) detail (relative noise 1.7); (3) bone (relative noise 4.5); and (4) edge (relative noise 7.7). A two Alternate Forced Choice (AFC) experimental paradigm was used to estimate the intensity needed to achieve 92% correct (i.e., I 92%). Four observers measured detection performance for five lesions with size ranging from 2.5 to 12.5 mm for each of these four reconstruction filters. Contrast detail curves obtained in images of an anthropomorphic phantom were not straight lines, but best fitted to a second order polynomial. Results from four readers show similar trends with modest inter-observer differences with the measured coefficient of variation of the absolute performance levels of ~22%. All reconstruction filters had similar shaped contrast detail curves except for smallest details where the frequency response of filters differed most significantly. Increasing the noise level always reduced detection performance, and a doubling of image noise resulted in an average drop in detection performance of ~20%. The key findings of this study are that (a) the Rose model can provide reasonable predictions as to how changes in lesion size affect observer detection; (b) the shape of CT contrast detail curves is affected only very slightly with reconstruction filter; (c) changes in reconstruction filter noise can predict qualitative changes in observer detection performance, but are poor direct predictors of the quantitative changes of imaging performance.

  8. Algebraic reconstruction techniques in CT and their implementation

    NASA Astrophysics Data System (ADS)

    Sun, Fengrong; Liu, Jiren; Zhu, Benren

    2001-09-01

    In the paper, we analyze comprehensively the mathematics of the Algebraic Reconstruction Techniques (ART) in the Computerized Tomography (CT), obtain some illumining conclusions, and then we design the procedure of ART simulation. The experiment result is also presented in the paper.

  9. Accuracy of quantitative reconstructions in SPECT/CT imaging

    NASA Astrophysics Data System (ADS)

    Shcherbinin, S.; Celler, A.; Belhocine, T.; van der Werf, R.; Driedger, A.

    2008-09-01

    The goal of this study was to determine the quantitative accuracy of our OSEM-APDI reconstruction method based on SPECT/CT imaging for Tc-99m, In-111, I-123, and I-131 isotopes. Phantom studies were performed on a SPECT/low-dose multislice CT system (Infinia-Hawkeye-4 slice, GE Healthcare) using clinical acquisition protocols. Two radioactive sources were centrally and peripherally placed inside an anthropometric Thorax phantom filled with non-radioactive water. Corrections for attenuation, scatter, collimator blurring and collimator septal penetration were applied and their contribution to the overall accuracy of the reconstruction was evaluated. Reconstruction with the most comprehensive set of corrections resulted in activity estimation with error levels of 3-5% for all the isotopes.

  10. Efficient iterative image reconstruction algorithm for dedicated breast CT

    NASA Astrophysics Data System (ADS)

    Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan

    2016-03-01

    Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.

  11. Spectrotemporal CT data acquisition and reconstruction at low dose

    SciTech Connect

    Clark, Darin P.; Badea, Cristian T.; Lee, Chang-Lung; Kirsch, David G.

    2015-11-15

    Purpose: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D + dual energy + time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. Methods: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction

  12. Fast reconstruction of low dose proton CT by sinogram interpolation

    NASA Astrophysics Data System (ADS)

    Hansen, David C.; Sangild Sørensen, Thomas; Rit, Simon

    2016-08-01

    Proton computed tomography (CT) has been demonstrated as a promising image modality in particle therapy planning. It can reduce errors in particle range calculations and consequently improve dose calculations. Obtaining a high imaging resolution has traditionally required computationally expensive iterative reconstruction techniques to account for the multiple scattering of the protons. Recently, techniques for direct reconstruction have been developed, but these require a higher imaging dose than the iterative methods. No previous work has compared the image quality of the direct and the iterative methods. In this article, we extend the methodology for direct reconstruction to be applicable for low imaging doses and compare the obtained results with three state-of-the-art iterative algorithms. We find that the direct method yields comparable resolution and image quality to the iterative methods, even at 1 mSv dose levels, while yielding a twentyfold speedup in reconstruction time over previously published iterative algorithms.

  13. Joint regularization for spectro-temporal CT reconstruction

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Badea, C. T.

    2016-03-01

    X-ray CT is widely used, both clinically and preclinically, for fast, high-resolution, anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. In previous work, we proposed and demonstrated a projection acquisition and reconstruction strategy for 5D CT (3D + dual-energy + time) which recovered spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. The approach relied on the approximate separability of the temporal and spectral reconstruction sub-problems, which enabled substantial projection undersampling and effective regularization. Here, we extend this previous work to more general, nonseparable 5D CT reconstruction cases (3D + muti-energy + time) with applicability to K-edge imaging of exogenous contrast agents. We apply the newly proposed algorithm in phantom simulations using a realistic system and noise model for a photon counting x-ray detector with six energy thresholds. The MOBY mouse phantom used contains realistic concentrations of iodine, gold, and calcium in water. Relative to weighted least-squares reconstruction, the proposed 5D reconstruction algorithm improved reconstruction and material decomposition accuracy by 3-18 times. Furthermore, by exploiting joint, low rank image structure between time points and energies, ~80 HU of contrast associated with the Kedge of gold and ~35 HU of contrast associated with the blood pool and myocardium were recovered from more than 400 HU of noise.

  14. Superiorization-based multi-energy CT image reconstruction

    NASA Astrophysics Data System (ADS)

    Yang, Q.; Cong, W.; Wang, G.

    2017-04-01

    The recently-developed superiorization approach is efficient and robust for solving various constrained optimization problems. This methodology can be applied to multi-energy CT image reconstruction with the regularization in terms of the prior rank, intensity and sparsity model (PRISM). In this paper, we propose a superiorized version of the simultaneous algebraic reconstruction technique (SART) based on the PRISM model. Then, we compare the proposed superiorized algorithm with the Split-Bregman algorithm in numerical experiments. The results show that both the Superiorized-SART and the Split-Bregman algorithms generate good results with weak noise and reduced artefacts.

  15. Tensor-based Dictionary Learning for Spectral CT Reconstruction

    PubMed Central

    Zhang, Yanbo; Wang, Ge

    2016-01-01

    Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628

  16. Towards an inline reconstruction architecture for micro-CT systems

    NASA Astrophysics Data System (ADS)

    Brasse, David; Humbert, Bernard; Mathelin, Carole; Rio, Marie-Christine; Guyonnet, Jean-Louis

    2005-12-01

    Recent developments in micro-CT have revolutionized the ability to examine in vivo living experimental animal models such as mouse with a spatial resolution less than 50 µm. The main requirements of in vivo imaging for biological researchers are a good spatial resolution, a low dose induced to the animal during the full examination and a reduced acquisition and reconstruction time for screening purposes. We introduce inline acquisition and reconstruction architecture to obtain in real time the 3D attenuation map of the animal fulfilling the three previous requirements. The micro-CT system is based on commercially available x-ray detector and micro-focus x-ray source. The reconstruction architecture is based on a cluster of PCs where a dedicated communication scheme combining serial and parallel treatments is implemented. In order to obtain high performance transmission rate between the detector and the reconstruction architecture, a dedicated data acquisition system is also developed. With the proposed solution, the time required to filter and backproject a projection of 2048 × 2048 pixels inside a volume of 140 mega voxels using the Feldkamp algorithm is similar to 500 ms, the time needed to acquire the same projection. Patent no. FR 05 02564 deposited 15 March 2005.

  17. Gamma regularization based reconstruction for low dose CT.

    PubMed

    Zhang, Junfeng; Chen, Yang; Hu, Yining; Luo, Limin; Shu, Huazhong; Li, Bicao; Liu, Jin; Coatrieux, Jean-Louis

    2015-09-07

    Reducing the radiation in computerized tomography is today a major concern in radiology. Low dose computerized tomography (LDCT) offers a sound way to deal with this problem. However, more severe noise in the reconstructed CT images is observed under low dose scan protocols (e.g. lowered tube current or voltage values). In this paper we propose a Gamma regularization based algorithm for LDCT image reconstruction. This solution is flexible and provides a good balance between the regularizations based on l0-norm and l1-norm. We evaluate the proposed approach using the projection data from simulated phantoms and scanned Catphan phantoms. Qualitative and quantitative results show that the Gamma regularization based reconstruction can perform better in both edge-preserving and noise suppression when compared with other norms.

  18. Iterative CT reconstruction using shearlet-based regularization

    NASA Astrophysics Data System (ADS)

    Vandeghinste, Bert; Goossens, Bart; Van Holen, Roel; Vanhove, Christian; Pizurica, Aleksandra; Vandenberghe, Stefaan; Staelens, Steven

    2012-03-01

    In computerized tomography, it is important to reduce the image noise without increasing the acquisition dose. Extensive research has been done into total variation minimization for image denoising and sparse-view reconstruction. However, TV minimization methods show superior denoising performance for simple images (with little texture), but result in texture information loss when applied to more complex images. Since in medical imaging, we are often confronted with textured images, it might not be beneficial to use TV. Our objective is to find a regularization term outperforming TV for sparse-view reconstruction and image denoising in general. A recent efficient solver was developed for convex problems, based on a split-Bregman approach, able to incorporate regularization terms different from TV. In this work, a proof-of-concept study demonstrates the usage of the discrete shearlet transform as a sparsifying transform within this solver for CT reconstructions. In particular, the regularization term is the 1-norm of the shearlet coefficients. We compared our newly developed shearlet approach to traditional TV on both sparse-view and on low-count simulated and measured preclinical data. Shearlet-based regularization does not outperform TV-based regularization for all datasets. Reconstructed images exhibit small aliasing artifacts in sparse-view reconstruction problems, but show no staircasing effect. This results in a slightly higher resolution than with TV-based regularization.

  19. Clinical outcomes in cervical cancer patients treated by FDG-PET/CT-based 3-dimensional planning for the first brachytherapy session

    PubMed Central

    Oh, Dongryul; Huh, Seung Jae; Park, Won; Ju, Sang Gyu; Nam, Heerim; Lee, Jeong Eun

    2016-01-01

    Abstract The aim of the study was to evaluate the treatment outcomes in cervical cancer patients treated with 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT)-guided 3-dimensional brachytherapy (3D-BT) planning for the first brachytherapy session. We retrospectively analyzed 87 patients with cervical cancer who received definitive radiotherapy (RT). Primary tumor size was ≤4 cm in 22 patients (25.3%), >4 cm and ≤6 cm in 45 patients (51.7%), and >6 cm in 20 patients (23.0%). The median total dose of external beam RT was 50.4 (50.4–60.4) Gy. FDG-PET/CT-guided 3D-BT with an iridium-192 source was performed. The clinical target volume (CTV) for 3D-BT included the entire cervix and the abnormal FDG-uptake with a 1-cm expansion. A planned total dose was 24 Gy at 4 Gy per insertion 3 times per week using a tandem and 2 ovoids. The mean D95 and D90 for the CTV were 73.4 (±5.9) Gy and 77.9 (±6.9) Gy, respectively (EQD2, α/β=10). The D2cc for the rectum and bladder was 374 (±97.4) cGy and 394 (±107.6) cGy per fraction, respectively. The EQD2 (α/β=3) for the D2cc was 74.5 (±12.4) Gy for the rectum and 77.3 (±14.6) Gy for the bladder. The median follow-up period was 40 (8–61) months. The 3-year overall survival (OS), progression-free survival (PFS), and local control (LC) rates were 84.7%, 72.1%, and 89.2%, respectively. The 3-year LC rate was 100% for tumors ≤ 4 cm, 91.1% for tumors > 4 cm and ≤ 6 cm, and 70.5% for tumors > 6 cm (P = 0.014). Local failure developed in 9 patients. Three patients had local failures outside of the CTV. Grade 1, 2, and 3 rectal bleeding developed in 5, 4, and 2 patients, respectively. One patient experienced rectovaginal fistula. FDG-PET/CT-guided 3D-BT planning is a feasible approach, which showed favorable clinical outcomes. PMID:27336876

  20. An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging.

    PubMed

    Van Eyndhoven, Geert; Batenburg, K Joost; Kazantsev, Daniil; Van Nieuwenhove, Vincent; Lee, Peter D; Dobson, Katherine J; Sijbers, Jan

    2015-11-01

    The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique. In this paper, a new iterative CT reconstruction algorithm for improved a temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. First, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Second, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary. Quantitative and qualitative results on different simulation experiments and a real neutron tomography data set show that, in comparison with the state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, the temporal resolution can be substantially increased, and thus fluid flow experiments with faster dynamics can be performed.

  1. A biological phantom for evaluation of CT image reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Cammin, J.; Fung, G. S. K.; Fishman, E. K.; Siewerdsen, J. H.; Stayman, J. W.; Taguchi, K.

    2014-03-01

    In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.

  2. Investigation of statistical iterative reconstruction for dedicated breast CT

    SciTech Connect

    Makeev, Andrey; Glick, Stephen J.

    2013-08-15

    Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue.Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters.Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved

  3. Investigation of statistical iterative reconstruction for dedicated breast CT

    PubMed Central

    Makeev, Andrey; Glick, Stephen J.

    2013-01-01

    Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue. Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters. Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved

  4. CT reconstruction techniques for improved accuracy of lung CT airway measurement

    SciTech Connect

    Rodriguez, A.; Ranallo, F. N.; Judy, P. F.; Gierada, D. S.; Fain, S. B.

    2014-11-01

    Purpose: To determine the impact of constrained reconstruction techniques on quantitative CT (qCT) of the lung parenchyma and airways for low x-ray radiation dose. Methods: Measurement of small airways with qCT remains a challenge, especially for low x-ray dose protocols. Images of the COPDGene quality assurance phantom (CTP698, The Phantom Laboratory, Salem, NY) were obtained using a GE discovery CT750 HD scanner for helical scans at x-ray radiation dose-equivalents ranging from 1 to 4.12 mSv (12–100 mA s current–time product). Other parameters were 40 mm collimation, 0.984 pitch, 0.5 s rotation, and 0.625 mm thickness. The phantom was sandwiched between 7.5 cm thick water attenuating phantoms for a total length of 20 cm to better simulate the scatter conditions of patient scans. Image data sets were reconstructed using STANDARD (STD), DETAIL, BONE, and EDGE algorithms for filtered back projection (FBP), 100% adaptive statistical iterative reconstruction (ASIR), and Veo reconstructions. Reduced (half) display field of view (DFOV) was used to increase sampling across airway phantom structures. Inner diameter (ID), wall area percent (WA%), and wall thickness (WT) measurements of eight airway mimicking tubes in the phantom, including a 2.5 mm ID (42.6 WA%, 0.4 mm WT), 3 mm ID (49.0 WA%, 0.6 mm WT), and 6 mm ID (49.0 WA%, 1.2 mm WT) were performed with Airway Inspector (Surgical Planning Laboratory, Brigham and Women’s Hospital, Boston, MA) using the phase congruency edge detection method. The average of individual measures at five central slices of the phantom was taken to reduce measurement error. Results: WA% measures were greatly overestimated while IDs were underestimated for the smaller airways, especially for reconstructions at full DFOV (36 cm) using the STD kernel, due to poor sampling and spatial resolution (0.7 mm pixel size). Despite low radiation dose, the ID of the 6 mm ID airway was consistently measured accurately for all methods other than STD

  5. CT reconstruction techniques for improved accuracy of lung CT airway measurement

    PubMed Central

    Rodriguez, A.; Ranallo, F. N.; Judy, P. F.; Gierada, D. S.; Fain, S. B.

    2014-01-01

    Purpose: To determine the impact of constrained reconstruction techniques on quantitative CT (qCT) of the lung parenchyma and airways for low x-ray radiation dose. Methods: Measurement of small airways with qCT remains a challenge, especially for low x-ray dose protocols. Images of the COPDGene quality assurance phantom (CTP698, The Phantom Laboratory, Salem, NY) were obtained using a GE discovery CT750 HD scanner for helical scans at x-ray radiation dose-equivalents ranging from 1 to 4.12 mSv (12–100 mA s current–time product). Other parameters were 40 mm collimation, 0.984 pitch, 0.5 s rotation, and 0.625 mm thickness. The phantom was sandwiched between 7.5 cm thick water attenuating phantoms for a total length of 20 cm to better simulate the scatter conditions of patient scans. Image data sets were reconstructed using STANDARD (STD), DETAIL, BONE, and EDGE algorithms for filtered back projection (FBP), 100% adaptive statistical iterative reconstruction (ASIR), and Veo reconstructions. Reduced (half) display field of view (DFOV) was used to increase sampling across airway phantom structures. Inner diameter (ID), wall area percent (WA%), and wall thickness (WT) measurements of eight airway mimicking tubes in the phantom, including a 2.5 mm ID (42.6 WA%, 0.4 mm WT), 3 mm ID (49.0 WA%, 0.6 mm WT), and 6 mm ID (49.0 WA%, 1.2 mm WT) were performed with Airway Inspector (Surgical Planning Laboratory, Brigham and Women’s Hospital, Boston, MA) using the phase congruency edge detection method. The average of individual measures at five central slices of the phantom was taken to reduce measurement error. Results: WA% measures were greatly overestimated while IDs were underestimated for the smaller airways, especially for reconstructions at full DFOV (36 cm) using the STD kernel, due to poor sampling and spatial resolution (0.7 mm pixel size). Despite low radiation dose, the ID of the 6 mm ID airway was consistently measured accurately for all methods other than STD

  6. Test of 3D CT reconstructions by EM + TV algorithm from undersampled data

    SciTech Connect

    Evseev, Ivan; Ahmann, Francielle; Silva, Hamilton P. da

    2013-05-06

    Computerized tomography (CT) plays an important role in medical imaging for diagnosis and therapy. However, CT imaging is connected with ionization radiation exposure of patients. Therefore, the dose reduction is an essential issue in CT. In 2011, the Expectation Maximization and Total Variation Based Model for CT Reconstruction (EM+TV) was proposed. This method can reconstruct a better image using less CT projections in comparison with the usual filtered back projection (FBP) technique. Thus, it could significantly reduce the overall dose of radiation in CT. This work reports the results of an independent numerical simulation for cone beam CT geometry with alternative virtual phantoms. As in the original report, the 3D CT images of 128 Multiplication-Sign 128 Multiplication-Sign 128 virtual phantoms were reconstructed. It was not possible to implement phantoms with lager dimensions because of the slowness of code execution even by the CORE i7 CPU.

  7. Dependence of Coronary 3-Dimensional Dose Maps on Coronary Topologies and Beam Set in Breast Radiation Therapy: A Study Based on CT Angiographies

    SciTech Connect

    Moignier, Alexandra; Girinsky, Théodore; Paul, Jean-François; and others

    2014-05-01

    Purpose: In left-side breast radiation therapy (RT), doses to the left main (LM) and left anterior descending (LAD) coronary arteries are usually assessed after delineation by prior anatomic knowledge on the treatment planning computed tomography (CT) scan. In this study, dose sensitivity due to interindividual coronary topology variation was assessed, and hot spots were located. Methods and Materials: Twenty-two detailed heart models, created from heart computed tomography angiographies, were fitted into a single representative female thorax. Two breast RT protocols were then simulated into a treatment planning system: the first protocol comprised tangential and tumoral bed beams (TGs{sub T}B) at 50 + 16 Gy, the second protocol added internal mammary chain beams at 50 Gy to TGs{sub T}B (TGs{sub T}B{sub I}MC). For the heart, the LAD, and the LM, several dose indicators were calculated: dose-volume histograms, mean dose (D{sub mean}), minimal dose received by the most irradiated 2% of the volume (D{sub 2%}), and 3-dimensional (3D) dose maps. Variations of these indicators with anatomies were studied. Results: For the LM, the intermodel dispersion of D{sub mean} and D{sub 2%} was 10% and 11%, respectively, with TGs{sub T}B and 40% and 80%, respectively, with TGs{sub T}B{sub I}MC. For the LAD, these dispersions were 19% (D{sub mean}) and 49% (D{sub 2%}) with TGs{sub T}B and 35% (D{sub mean}) and 76% (D{sub 2%}) with TGs{sub T}B{sub I}MC. The 3D dose maps revealed that the internal mammary chain beams induced hot spots between 20 and 30 Gy on the LM and the proximal LAD for some coronary topologies. Without IMC beams, hot spots between 5 and 26 Gy are located on the middle and distal LAD. Conclusions: Coronary dose distributions with hot spot location and dose level can change significantly depending on coronary topology, as highlighted by 3D coronary dose maps. In clinical practice, coronary imaging may be required for a relevant coronary dose assessment

  8. Task-based optimization of image reconstruction in breast CT

    NASA Astrophysics Data System (ADS)

    Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

    2014-03-01

    We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.

  9. A feature refinement approach for statistical interior CT reconstruction.

    PubMed

    Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

    2016-07-21

    Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)-minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

  10. A feature refinement approach for statistical interior CT reconstruction

    NASA Astrophysics Data System (ADS)

    Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

    2016-07-01

    Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)—minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

  11. Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

    PubMed Central

    Grosser, Oliver S.; Kupitz, Dennis; Ruf, Juri; Czuczwara, Damian; Steffen, Ingo G.; Furth, Christian; Thormann, Markus; Loewenthal, David; Ricke, Jens; Amthauer, Holger

    2015-01-01

    Background Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images. Methodology/Principal Findings Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001). Conclusion/Significance In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality. PMID:26390216

  12. Low dose dynamic myocardial CT perfusion using advanced iterative reconstruction

    NASA Astrophysics Data System (ADS)

    Eck, Brendan L.; Fahmi, Rachid; Fuqua, Christopher; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

    2015-03-01

    Dynamic myocardial CT perfusion (CTP) can provide quantitative functional information for the assessment of coronary artery disease. However, x-ray dose in dynamic CTP is high, typically from 10mSv to >20mSv. We compared the dose reduction potential of advanced iterative reconstruction, Iterative Model Reconstruction (IMR, Philips Healthcare, Cleveland, Ohio) to hybrid iterative reconstruction (iDose4) and filtered back projection (FBP). Dynamic CTP scans were obtained using a porcine model with balloon-induced ischemia in the left anterior descending coronary artery to prescribed fractional flow reserve values. High dose dynamic CTP scans were acquired at 100kVp/100mAs with effective dose of 23mSv. Low dose scans at 75mAs, 50mAs, and 25mAs were simulated by adding x-ray quantum noise and detector electronic noise to the projection space data. Images were reconstructed with FBP, iDose4, and IMR at each dose level. Image quality in static CTP images was assessed by SNR and CNR. Blood flow was obtained using a dynamic CTP analysis pipeline and blood flow image quality was assessed using flow-SNR and flow-CNR. IMR showed highest static image quality according to SNR and CNR. Blood flow in FBP was increasingly over-estimated at reduced dose. Flow was more consistent for iDose4 from 100mAs to 50mAs, but was over-estimated at 25mAs. IMR was most consistent from 100mAs to 25mAs. Static images and flow maps for 100mAs FBP, 50mAs iDose4, and 25mAs IMR showed comparable, clear ischemia, CNR, and flow-CNR values. These results suggest that IMR can enable dynamic CTP at significantly reduced dose, at 5.8mSv or 25% of the comparable 23mSv FBP protocol.

  13. SU-E-I-73: Clinical Evaluation of CT Image Reconstructed Using Interior Tomography

    SciTech Connect

    Zhang, J; Ge, G; Winkler, M; Cong, W; Wang, G

    2014-06-01

    Purpose: Radiation dose reduction has been a long standing challenge in CT imaging of obese patients. Recent advances in interior tomography (reconstruction of an interior region of interest (ROI) from line integrals associated with only paths through the ROI) promise to achieve significant radiation dose reduction without compromising image quality. This study is to investigate the application of this technique in CT imaging through evaluating imaging quality reconstructed from patient data. Methods: Projection data were directly obtained from patients who had CT examinations in a Dual Source CT scanner (DSCT). Two detectors in a DSCT acquired projection data simultaneously. One detector provided projection data for full field of view (FOV, 50 cm) while another detectors provided truncated projection data for a FOV of 26 cm. Full FOV CT images were reconstructed using both filtered back projection and iterative algorithm; while interior tomography algorithm was implemented to reconstruct ROI images. For comparison reason, FBP was also used to reconstruct ROI images. Reconstructed CT images were evaluated by radiologists and compared with images from CT scanner. Results: The results show that the reconstructed ROI image was in excellent agreement with the truth inside the ROI, obtained from images from CT scanner, and the detailed features in the ROI were quantitatively accurate. Radiologists evaluation shows that CT images reconstructed with interior tomography met diagnosis requirements. Radiation dose may be reduced up to 50% using interior tomography, depending on patient size. Conclusion: This study shows that interior tomography can be readily employed in CT imaging for radiation dose reduction. It may be especially useful in imaging obese patients, whose subcutaneous tissue is less clinically relevant but may significantly increase radiation dose.

  14. Iterative ct reconstruction from few projections for the nondestructive post irradiation examination of nuclear fuel assemblies

    NASA Astrophysics Data System (ADS)

    Abir, Muhammad Imran Khan

    The core components (e.g. fuel assemblies, spacer grids, control rods) of the nuclear reactors encounter harsh environment due to high temperature, physical stress, and a tremendous level of radiation. The integrity of these elements is crucial for safe operation of the nuclear power plants. The Post Irradiation Examination (PIE) can reveal information about the integrity of the elements during normal operations and off?normal events. Computed tomography (CT) is a tool for evaluating the structural integrity of elements non-destructively. CT requires many projections to be acquired from different view angles after which a mathematical algorithm is adopted for reconstruction. Obtaining many projections is laborious and expensive in nuclear industries. Reconstructions from a small number of projections are explored to achieve faster and cost-efficient PIE. Classical reconstruction algorithms (e.g. filtered back projection) cannot offer stable reconstructions from few projections and create severe streaking artifacts. In this thesis, conventional algorithms are reviewed, and new algorithms are developed for reconstructions of the nuclear fuel assemblies using few projections. CT reconstruction from few projections falls into two categories: the sparse-view CT and the limited-angle CT or tomosynthesis. Iterative reconstruction algorithms are developed for both cases in the field of compressed sensing (CS). The performance of the algorithms is assessed using simulated projections and validated through real projections. The thesis also describes the systematic strategy towards establishing the conditions of reconstructions and finds the optimal imaging parameters for reconstructions of the fuel assemblies from few projections.

  15. Texture-preserving Bayesian image reconstruction for low-dose CT

    NASA Astrophysics Data System (ADS)

    Zhang, Hao; Han, Hao; Hu, Yifan; Liu, Yan; Ma, Jianhua; Li, Lihong; Moore, William; Liang, Zhengrong

    2016-03-01

    Markov random field (MRF) model has been widely used in Bayesian image reconstruction to reconstruct piecewise smooth images in the presence of noise, such as in low-dose X-ray computed tomography (LdCT). While it can preserve edge sharpness via edge-preserving potential function, its regional smoothing may sacrifice tissue image textures, which have been recognized as useful imaging biomarkers, and thus it compromises clinical tasks such as differentiating malignant vs. benign lesions, e.g., lung nodule or colon polyp. This study aims to shift the edge preserving regional noise smoothing paradigm to texture-preserving framework for LdCT image reconstruction while retaining the advantage of MRF's neighborhood system on edge preservation. Specifically, we adapted the MRF model to incorporate the image textures of lung, bone, fat, muscle, etc. from previous full-dose CT scan as a priori knowledge for texture-preserving Bayesian reconstruction of current LdCT images. To show the feasibility of proposed reconstruction framework, experiments using clinical patient scans (with lung nodule or colon polyp) were conducted. The experimental outcomes showed noticeable gain by the a priori knowledge for LdCT image reconstruction with the well-known Haralick texture measures. Thus, it is conjectured that texture-preserving LdCT reconstruction has advantages over edge-preserving regional smoothing paradigm for texture-specific clinical applications.

  16. Ultralow dose computed tomography attenuation correction for pediatric PET CT using adaptive statistical iterative reconstruction

    SciTech Connect

    Brady, Samuel L.; Shulkin, Barry L.

    2015-02-15

    Purpose: To develop ultralow dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultralow doses (10–35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUV{sub bw}) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. Results: CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUV{sub bw}, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3–0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. Conclusions: Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake.

  17. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy.

    PubMed

    Lee, Chae Young; Song, Hankyeol; Park, Chan Woo; Chung, Yong Hyun; Kim, Jin Sung; Park, Justin C

    2016-01-01

    The purposes of this study were to optimize a proton computed tomography system (pCT) for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT) 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy.

  18. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy

    PubMed Central

    Lee, Chae Young; Song, Hankyeol; Park, Chan Woo; Chung, Yong Hyun; Park, Justin C.

    2016-01-01

    The purposes of this study were to optimize a proton computed tomography system (pCT) for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT) 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy. PMID:27243822

  19. Helical mode lung 4D-CT reconstruction using Bayesian model.

    PubMed

    He, Tiancheng; Xue, Zhong; Nitsch, Paige L; Teh, Bin S; Wong, Stephen T

    2013-01-01

    4D computed tomography (CT) has been widely used for treatment planning of thoracic and abdominal cancer radiotherapy. Current 4D-CT lung image reconstruction methods rely on respiratory gating to rearrange the large number of axial images into different phases, which may be subject to external surrogate errors due to poor reproducibility of breathing cycles. New image-matching-based reconstruction works better for the cine mode of 4D-CT acquisition than the helical mode because the table position of each axial image is different in helical mode and image matching might suffer from bigger errors. In helical mode, not only the phases but also the un-uniform table positions of images need to be considered. We propose a Bayesian method for automated 4D-CT lung image reconstruction in helical mode 4D scans. Each axial image is assigned to a respiratory phase based on the Bayesian framework that ensures spatial and temporal smoothness of surfaces of anatomical structures. Iterative optimization is used to reconstruct a series of 3D-CT images for subjects undergoing 4D scans. In experiments, we compared visually and quantitatively the results of the proposed Bayesian 4D-CT reconstruction algorithm with the respiratory surrogate and the image matching-based method. The results showed that the proposed algorithm yielded better 4D-CT for helical scans.

  20. Region-of-interest reconstruction for a cone-beam dental CT with a circular trajectory

    NASA Astrophysics Data System (ADS)

    Hu, Zhanli; Zou, Jing; Gui, Jianbao; Zheng, Hairong; Xia, Dan

    2013-04-01

    Dental CT is the most appropriate and accurate device for preoperative evaluation of dental implantation. It can demonstrate the quantity of bone in three dimensions (3D), the location of important adjacent anatomic structures and the quality of available bone with minimal geometric distortion. Nevertheless, with the rapid increase of dental CT examinations, we are facing the problem of dose reduction without loss of image quality. In this work, backprojection-filtration (BPF) and Feldkamp-Davis-Kress (FDK) algorithm was applied to reconstruct the 3D full image and region-of-interest (ROI) image from complete and truncated circular cone-beam data respectively by computer-simulation. In addition, the BPF algorithm was evaluated based on the 3D ROI-image reconstruction from real data, which was acquired from our developed circular cone-beam prototype dental CT system. The results demonstrated that the ROI-image quality reconstructed from truncated data using the BPF algorithm was comparable to that reconstructed from complete data. The FDK algorithm, however, created artifacts while reconstructing ROI-image. Thus it can be seen, for circular cone-beam dental CT, reducing scanning angular range of the BPF algorithm used for ROI-image reconstruction are helpful for reducing the radiation dose and scanning time. Finally, an analytical method was developed for estimation of the ROI projection area on the detector before CT scanning, which would help doctors to roughly estimate the total radiation dose before the CT examination.

  1. Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

    NASA Astrophysics Data System (ADS)

    McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

    2006-03-01

    To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the

  2. MicroCT: Semi-Automated Analysis of CT Reconstructed Data of Home Made Explosive Materials Using the Matlab MicroCT Analysis GUI

    SciTech Connect

    Seetho, I M; Brown, W D; Kallman, J S; Martz, H E; White, W T

    2011-09-22

    This Standard Operating Procedure (SOP) provides the specific procedural steps for analyzing reconstructed CT images obtained under the IDD Standard Operating Procedures for data acquisition [1] and MicroCT image reconstruction [2], per the IDD Quality Assurance Plan for MicroCT Scanning [3]. Although intended to apply primarily to MicroCT data acquired in the HEAFCAT Facility at LLNL, these procedures may also be applied to data acquired at Tyndall from the YXLON cabinet and at TSL from the HEXCAT system. This SOP also provides the procedural steps for preparing the tables and graphs to be used in the reporting of analytical results. This SOP applies to R and D work - for production applications, use [4].

  3. MicroCT: Automated Analysis of CT Reconstructed Data of Home Made Explosive Materials Using the Matlab MicroCT Analysis GUI

    SciTech Connect

    Seetho, I M; Brown, W D; Kallman, J S; Martz, H E; White, W T

    2011-09-22

    This Standard Operating Procedure (SOP) provides the specific procedural steps for analyzing reconstructed CT images obtained under the IDD Standard Operating Procedures for data acquisition [1] and MicroCT image reconstruction [2], per the IDD Quality Assurance Plan for MicroCT Scanning [3]. Although intended to apply primarily to MicroCT data acquired in the HEAFCAT Facility at LLNL, these procedures may also be applied to data acquired at Tyndall from the YXLON cabinet and at TSL from the HEXCAT system. This SOP also provides the procedural steps for preparing the tables and graphs to be used in the reporting of analytical results. This SOP applies to production work - for R and D there are two other semi-automated methods as given in [4, 5].

  4. Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

    2015-09-01

    For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose

  5. Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms.

    PubMed

    Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M; Asma, Evren; Kinahan, Paul E; De Man, Bruno

    2015-10-07

    For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition.We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality.With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels

  6. Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT

    SciTech Connect

    Matenine, Dmitri Mascolo-Fortin, Julia; Goussard, Yves

    2015-11-15

    Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can

  7. In-line phase contrast micro-CT reconstruction for biomedical specimens.

    PubMed

    Fu, Jian; Tan, Renbo

    2014-01-01

    X-ray phase contrast micro computed tomography (micro-CT) can non-destructively provide the internal structure information of soft tissues and low atomic number materials. It has become an invaluable analysis tool for biomedical specimens. Here an in-line phase contrast micro-CT reconstruction technique is reported, which consists of a projection extraction method and the conventional filter back-projection (FBP) reconstruction algorithm. The projection extraction is implemented by applying the Fourier transform to the forward projections of in-line phase contrast micro-CT. This work comprises a numerical study of the method and its experimental verification using a biomedical specimen dataset measured at an X-ray tube source micro-CT setup. The numerical and experimental results demonstrate that the presented technique can improve the imaging contrast of biomedical specimens. It will be of interest for a wide range of in-line phase contrast micro-CT applications in medicine and biology.

  8. Automated cardiac motion compensation in PET/CT for accurate reconstruction of PET myocardial perfusion images

    NASA Astrophysics Data System (ADS)

    Khurshid, Khawar; McGough, Robert J.; Berger, Kevin

    2008-10-01

    Error-free reconstruction of PET data with a registered CT attenuation map is essential for accurate quantification and interpretation of cardiac perfusion. Misalignment of the CT and PET data can produce an erroneous attenuation map that projects lung attenuation parameters onto the heart wall, thereby underestimating the attenuation and creating artifactual areas of hypoperfusion that can be misinterpreted as myocardial ischemia or infarction. The major causes of misregistration between CT and PET images are the respiratory motion, cardiac motion and gross physical motion of the patient. The misalignment artifact problem is overcome with automated cardiac registration software that minimizes the alignment error between the two modalities. Results show that the automated registration process works equally well for any respiratory phase in which the CT scan is acquired. Further evaluation of this procedure on 50 patients demonstrates that the automated registration software consistently aligns the two modalities, eliminating artifactual hypoperfusion in reconstructed PET images due to PET/CT misregistration. With this registration software, only one CT scan is required for PET/CT imaging, which reduces the radiation dose required for CT-based attenuation correction and improves the clinical workflow for PET/CT.

  9. Image reconstruction for PET/CT scanners: past achievements and future challenges

    PubMed Central

    Tong, Shan; Alessio, Adam M; Kinahan, Paul E

    2011-01-01

    PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. PMID:21339831

  10. Evaluation of accelerated iterative x-ray CT image reconstruction using floating point graphics hardware

    NASA Astrophysics Data System (ADS)

    Kole, J. S.; Beekman, F. J.

    2006-02-01

    Statistical reconstruction methods offer possibilities to improve image quality as compared with analytical methods, but current reconstruction times prohibit routine application in clinical and micro-CT. In particular, for cone-beam x-ray CT, the use of graphics hardware has been proposed to accelerate the forward and back-projection operations, in order to reduce reconstruction times. In the past, wide application of this texture hardware mapping approach was hampered owing to limited intrinsic accuracy. Recently, however, floating point precision has become available in the latest generation commodity graphics cards. In this paper, we utilize this feature to construct a graphics hardware accelerated version of the ordered subset convex reconstruction algorithm. The aims of this paper are (i) to study the impact of using graphics hardware acceleration for statistical reconstruction on the reconstructed image accuracy and (ii) to measure the speed increase one can obtain by using graphics hardware acceleration. We compare the unaccelerated algorithm with the graphics hardware accelerated version, and for the latter we consider two different interpolation techniques. A simulation study of a micro-CT scanner with a mathematical phantom shows that at almost preserved reconstructed image accuracy, speed-ups of a factor 40 to 222 can be achieved, compared with the unaccelerated algorithm, and depending on the phantom and detector sizes. Reconstruction from physical phantom data reconfirms the usability of the accelerated algorithm for practical cases.

  11. Evaluation of accelerated iterative x-ray CT image reconstruction using floating point graphics hardware.

    PubMed

    Kole, J S; Beekman, F J

    2006-02-21

    Statistical reconstruction methods offer possibilities to improve image quality as compared with analytical methods, but current reconstruction times prohibit routine application in clinical and micro-CT. In particular, for cone-beam x-ray CT, the use of graphics hardware has been proposed to accelerate the forward and back-projection operations, in order to reduce reconstruction times. In the past, wide application of this texture hardware mapping approach was hampered owing to limited intrinsic accuracy. Recently, however, floating point precision has become available in the latest generation commodity graphics cards. In this paper, we utilize this feature to construct a graphics hardware accelerated version of the ordered subset convex reconstruction algorithm. The aims of this paper are (i) to study the impact of using graphics hardware acceleration for statistical reconstruction on the reconstructed image accuracy and (ii) to measure the speed increase one can obtain by using graphics hardware acceleration. We compare the unaccelerated algorithm with the graphics hardware accelerated version, and for the latter we consider two different interpolation techniques. A simulation study of a micro-CT scanner with a mathematical phantom shows that at almost preserved reconstructed image accuracy, speed-ups of a factor 40 to 222 can be achieved, compared with the unaccelerated algorithm, and depending on the phantom and detector sizes. Reconstruction from physical phantom data reconfirms the usability of the accelerated algorithm for practical cases.

  12. Region-of-interest image reconstruction in circular cone-beam microCT

    SciTech Connect

    Cho, Seungryong; Bian, Junguo; Pelizzari, Charles A.; Chen, C.-T.; He, T.-C.; Pan Xiaochuan

    2007-12-15

    Cone-beam microcomputed tomography (microCT) is one of the most popular choices for small animal imaging which is becoming an important tool for studying animal models with transplanted diseases. Region-of-interest (ROI) imaging techniques in CT, which can reconstruct an ROI image from the projection data set of the ROI, can be used not only for reducing imaging-radiation exposure to the subject and scatters to the detector but also for potentially increasing spatial resolution of the reconstructed images. Increasing spatial resolution in microCT images can facilitate improved accuracy in many assessment tasks. A method proposed previously for increasing CT image spatial resolution entails the exploitation of the geometric magnification in cone-beam CT. Due to finite detector size, however, this method can lead to data truncation for a large geometric magnification. The Feldkamp-Davis-Kress (FDK) algorithm yields images with artifacts when truncated data are used, whereas the recently developed backprojection filtration (BPF) algorithm is capable of reconstructing ROI images without truncation artifacts from truncated cone-beam data. We apply the BPF algorithm to reconstructing ROI images from truncated data of three different objects acquired by our circular cone-beam microCT system. Reconstructed images by use of the FDK and BPF algorithms from both truncated and nontruncated cone-beam data are compared. The results of the experimental studies demonstrate that, from certain truncated data, the BPF algorithm can reconstruct ROI images with quality comparable to that reconstructed from nontruncated data. In contrast, the FDK algorithm yields ROI images with truncation artifacts. Therefore, an implication of the studies is that, when truncated data are acquired with a configuration of a large geometric magnification, the BPF algorithm can be used for effective enhancement of the spatial resolution of a ROI image.

  13. Inter-observer agreement between 2-dimensional CT versus 3-dimensional I-Space model in the Diagnosis of Occult Scaphoid Fractures

    PubMed Central

    Drijkoningen, Tessa; Knoter, Robert; Coerkamp, Emile G.; Koning, Anton H.J.; Rhemrev, Steven J.; Beeres, Frank J.

    2016-01-01

    Background: The I-Space is a radiological imaging system in which Computed Tomography (CT)-scans can be evaluated as a three dimensional hologram. The aim of this study is to analyze the value of virtual reality (I-Space) in diagnosing acute occult scaphoid fractures. Methods: A convenient cohort of 24 patients with a CT-scan from prior studies, without a scaphoid fracture on radiograph, yet high clinical suspicion of a fracture, were included in this study. CT-scans were evaluated in the I-Space by 7 observers of which 3 observers assessed the scans in the I-Space twice. The observers in this study assessed in the I-Space whether the patient had a scaphoid fracture. The kappa value was calculated for inter- and intra-observer agreement. Results: The Kappa value varied from 0.11 to 0.33 for the first assessment. For the three observers who assessed the CT-scans twice; observer 1 improved from a kappa of 0.33 to 0.50 (95% CI 0.26-0.74, P=0.01), observer 2 from 0.17 to 0.78 (95% CI 0.36-1.0, P<0.001), and observer 3 from 0.11 to 0.24 (95% CI 0.0-0.77, P=0.24). Conclusion: Following our findings the I-Space has a fast learning curve and has a potential place in the diagnostic modalities for suspected scaphoid fractures. PMID:27847847

  14. Post-reconstruction non-local means filtering methods using CT side information for quantitative SPECT

    NASA Astrophysics Data System (ADS)

    Chun, Se Young; Fessler, Jeffrey A.; Dewaraja, Yuni K.

    2013-09-01

    Quantitative SPECT techniques are important for many applications including internal emitter therapy dosimetry where accurate estimation of total target activity and activity distribution within targets are both potentially important for dose-response evaluations. We investigated non-local means (NLM) post-reconstruction filtering for accurate I-131 SPECT estimation of both total target activity and the 3D activity distribution. We first investigated activity estimation versus number of ordered-subsets expectation-maximization (OSEM) iterations. We performed simulations using the XCAT phantom with tumors containing a uniform and a non-uniform activity distribution, and measured the recovery coefficient (RC) and the root mean squared error (RMSE) to quantify total target activity and activity distribution, respectively. We observed that using more OSEM iterations is essential for accurate estimation of RC, but may or may not improve RMSE. We then investigated various post-reconstruction filtering methods to suppress noise at high iteration while preserving image details so that both RC and RMSE can be improved. Recently, NLM filtering methods have shown promising results for noise reduction. Moreover, NLM methods using high-quality side information can improve image quality further. We investigated several NLM methods with and without CT side information for I-131 SPECT imaging and compared them to conventional Gaussian filtering and to unfiltered methods. We studied four different ways of incorporating CT information in the NLM methods: two known (NLM CT-B and NLM CT-M) and two newly considered (NLM CT-S and NLM CT-H). We also evaluated the robustness of NLM filtering using CT information to erroneous CT. NLM CT-S and NLM CT-H yielded comparable RC values to unfiltered images while substantially reducing RMSE. NLM CT-S achieved -2.7 to 2.6% increase of RC compared to no filtering and NLM CT-H yielded up to 6% decrease in RC while other methods yielded lower RCs

  15. Post-reconstruction non-local means filtering methods using CT side information for quantitative SPECT.

    PubMed

    Chun, Se Young; Fessler, Jeffrey A; Dewaraja, Yuni K

    2013-09-07

    Quantitative SPECT techniques are important for many applications including internal emitter therapy dosimetry where accurate estimation of total target activity and activity distribution within targets are both potentially important for dose–response evaluations. We investigated non-local means (NLM) post-reconstruction filtering for accurate I-131 SPECT estimation of both total target activity and the 3D activity distribution. We first investigated activity estimation versus number of ordered-subsets expectation–maximization (OSEM) iterations. We performed simulations using the XCAT phantom with tumors containing a uniform and a non-uniform activity distribution, and measured the recovery coefficient (RC) and the root mean squared error (RMSE) to quantify total target activity and activity distribution, respectively. We observed that using more OSEM iterations is essential for accurate estimation of RC, but may or may not improve RMSE. We then investigated various post-reconstruction filtering methods to suppress noise at high iteration while preserving image details so that both RC and RMSE can be improved. Recently, NLM filtering methods have shown promising results for noise reduction. Moreover, NLM methods using high-quality side information can improve image quality further. We investigated several NLM methods with and without CT side information for I-131 SPECT imaging and compared them to conventional Gaussian filtering and to unfiltered methods. We studied four different ways of incorporating CT information in the NLM methods: two known (NLM CT-B and NLM CT-M) and two newly considered (NLM CT-S and NLM CT-H). We also evaluated the robustness of NLM filtering using CT information to erroneous CT. NLM CT-S and NLM CT-H yielded comparable RC values to unfiltered images while substantially reducing RMSE. NLM CT-S achieved −2.7 to 2.6% increase of RC compared to no filtering and NLM CT-H yielded up to 6% decrease in RC while other methods yielded lower

  16. Low Dose CT Reconstruction via Edge-preserving Total Variation Regularization

    PubMed Central

    Tian, Zhen; Jia, Xun; Yuan, Kehong; Pan, Tinsu; Jiang, Steve B.

    2014-01-01

    High radiation dose in CT scans increases a lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with Total Variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing an energy consisting of an edge-preserving TV norm and a data fidelity term posed by the x-ray projections. The edge-preserving TV term is proposed to preferentially perform smoothing only on non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original total variation norm. During the reconstruction process, the pixels at edges would be gradually identified and given small penalty weight. Our iterative algorithm is implemented on GPU to improve its speed. We test our reconstruction algorithm on a digital NCAT phantom, a physical chest phantom, and a Catphan phantom. Reconstruction results from a conventional FBP algorithm and a TV regularization method without edge preserving penalty are also presented for comparison purpose. The experimental results illustrate that both TV-based algorithm and our edge-preserving TV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under the low dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low contrast structures and therefore maintain acceptable spatial resolution. PMID:21860076

  17. Low-dose CT reconstruction via edge-preserving total variation regularization

    NASA Astrophysics Data System (ADS)

    Tian, Zhen; Jia, Xun; Yuan, Kehong; Pan, Tinsu; Jiang, Steve B.

    2011-09-01

    High radiation dose in computed tomography (CT) scans increases the lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with total variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low-contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV (EPTV) regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing energy consisting of an EPTV norm and a data fidelity term posed by the x-ray projections. The EPTV term is proposed to preferentially perform smoothing only on the non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original TV norm. During the reconstruction process, the pixels at the edges would be gradually identified and given low penalty weight. Our iterative algorithm is implemented on graphics processing unit to improve its speed. We test our reconstruction algorithm on a digital NURBS-based cardiac-troso phantom, a physical chest phantom and a Catphan phantom. Reconstruction results from a conventional filtered backprojection (FBP) algorithm and a TV regularization method without edge-preserving penalty are also presented for comparison purposes. The experimental results illustrate that both the TV-based algorithm and our EPTV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under a low-dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low-contrast structures and therefore maintain acceptable spatial resolution.

  18. Sparse angular CT reconstruction using non-local means based iterative-correction POCS.

    PubMed

    Huang, Jing; Ma, Jianhua; Liu, Nan; Zhang, Hua; Bian, Zhaoying; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

    2011-04-01

    In divergent-beam computed tomography (CT), sparse angular sampling frequently leads to conspicuous streak artifacts. In this paper, we propose a novel non-local means (NL-means) based iterative-correction projection onto convex sets (POCS) algorithm, named as NLMIC-POCS, for effective and robust sparse angular CT reconstruction. The motivation for using NLMIC-POCS is that NL-means filtered image can produce an acceptable priori solution for sequential POCS iterative reconstruction. The NLMIC-POCS algorithm has been tested on simulated and real phantom data. The experimental results show that the presented NLMIC-POCS algorithm can significantly improve the image quality of the sparse angular CT reconstruction in suppressing streak artifacts and preserving the edges of the image.

  19. Combining ordered subsets and momentum for accelerated X-ray CT image reconstruction.

    PubMed

    Kim, Donghwan; Ramani, Sathish; Fessler, Jeffrey A

    2015-01-01

    Statistical X-ray computed tomography (CT) reconstruction can improve image quality from reduced dose scans, but requires very long computation time. Ordered subsets (OS) methods have been widely used for research in X-ray CT statistical image reconstruction (and are used in clinical PET and SPECT reconstruction). In particular, OS methods based on separable quadratic surrogates (OS-SQS) are massively parallelizable and are well suited to modern computing architectures, but the number of iterations required for convergence should be reduced for better practical use. This paper introduces OS-SQS-momentum algorithms that combine Nesterov's momentum techniques with OS-SQS methods, greatly improving convergence speed in early iterations. If the number of subsets is too large, the OS-SQS-momentum methods can be unstable, so we propose diminishing step sizes that stabilize the method while preserving the very fast convergence behavior. Experiments with simulated and real 3D CT scan data illustrate the performance of the proposed algorithms.

  20. Single-slice reconstruction method for helical cone-beam differential phase-contrast CT.

    PubMed

    Fu, Jian; Chen, Liyuan

    2014-01-01

    X-ray phase-contrast computed tomography (PC-CT) can provide the internal structure information of biomedical specimens with high-quality cross-section images and has become an invaluable analysis tool. Here a simple and fast reconstruction algorithm is reported for helical cone-beam differential PC-CT (DPC-CT), which is called the DPC-CB-SSRB algorithm. It combines the existing CB-SSRB method of helical cone-beam absorption-contrast CT with the differential nature of DPC imaging. The reconstruction can be performed using 2D fan-beam filtered back projection algorithm with the Hilbert imaginary filter. The quality of the results for large helical pitches is surprisingly good. In particular, with this algorithm comparable quality is obtained using helical cone-beam DPC-CT data with a normalized pitch of 10 to that obtained using the traditional inter-row interpolation reconstruction with a normalized pitch of 2. This method will push the future medical helical cone-beam DPC-CT imaging applications.

  1. A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT

    NASA Astrophysics Data System (ADS)

    Wang, Yingmei; Wang, Ge; Mao, Shuwei; Cong, Wenxiang; Ji, Zhilong; Cai, Jian-Feng; Ye, Yangbo

    2016-11-01

    Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ (r,E) at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. Our software solution requires no change on hardware of a CT machine. With the Shepp-Logan phantom, we have found that although the photoelectric and Compton components were not perfectly reconstructed, their composite effect was very accurately reconstructed as compared to the ground truth and the dual-energy CT counterpart. This means that our proposed method has an intrinsic benefit in beam hardening correction and metal artifact reduction. The algorithm is based on a nonlinear polychromatic acquisition model for x-ray CT. The key technique is a sparse representation of iterations in a framelet system. Convergence of the algorithm is studied. This is believed to be the first application of framelet imaging tools to a nonlinear inverse problem.

  2. Comparison of internal target volumes defined on 3-dimensional, 4-dimensonal, and cone-beam CT images of non-small-cell lung cancer

    PubMed Central

    Li, Fengxiang; Li, Jianbin; Ma, Zhifang; Zhang, Yingjie; Xing, Jun; Qi, Huanpeng; Shang, Dongping

    2016-01-01

    Purpose The purpose of this study was to compare the positional and volumetric differences of internal target volumes defined on three-dimensional computed tomography (3DCT), four-dimensional CT (4DCT), and cone-beam CT (CBCT) images of non-small-cell lung cancer (NSCLC). Materials and methods Thirty-one patients with NSCLC sequentially underwent 3DCT and 4DCT simulation scans of the thorax during free breathing. The first CBCT was performed and registered to the planning CT using the bony anatomy registration during radiotherapy. The gross tumor volumes were contoured on the basis of 3DCT, maximum intensity projection (MIP) of 4DCT, and CBCT. CTV3D (clinical target volume), internal target volumes, ITVMIP and ITVCBCT, were defined with a 7 mm margin accounting for microscopic disease. ITV10 mm and ITV5 mm were defined on the basis of CTV3D: ITV10 mm with a 5 mm margin in left–right (LR), anterior–posterior (AP) directions and 10 mm in cranial–caudal (CC) direction; ITV5 mm with an isotropic internal margin (IM) of 5 mm. The differences in the position, size, Dice’s similarity coefficient (DSC) and inclusion relation of different volumes were evaluated. Results The median size ratios of ITV10 mm, ITV5 mm, and ITVMIP to ITVCBCT were 2.33, 1.88, and 1.03, respectively, for tumors in the upper lobe and 2.13, 1.76, and 1.1, respectively, for tumors in the middle-lower lobe. The median DSCs of ITV10 mm, ITV5 mm, ITVMIP, and ITVCBCT were 0.6, 0.66, and 0.83 for all patients. The median percentages of ITVCBCT not included in ITV10 mm, ITV5 mm, and ITVMIP were 0.1%, 1.63%, and 15.21%, respectively, while the median percentages of ITV10 mm, ITV5 mm, and ITVMIP not included in ITVCBCT were 57.08%, 48.89%, and 20.04%, respectively. Conclusion The use of the individual ITV derived from 4DCT merely based on bony registration in radiotherapy may result in a target miss. The ITVs derived from 3DCT with isotropic margins have a good coverage of the ITV from CBCT, but the

  3. The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK)

    NASA Astrophysics Data System (ADS)

    Rit, S.; Vila Oliva, M.; Brousmiche, S.; Labarbe, R.; Sarrut, D.; Sharp, G. C.

    2014-03-01

    We propose the Reconstruction Toolkit (RTK, http://www.openrtk.org), an open-source toolkit for fast cone-beam CT reconstruction, based on the Insight Toolkit (ITK) and using GPU code extracted from Plastimatch. RTK is developed by an open consortium (see affiliations) under the non-contaminating Apache 2.0 license. The quality of the platform is daily checked with regression tests in partnership with Kitware, the company supporting ITK. Several features are already available: Elekta, Varian and IBA inputs, multi-threaded Feldkamp-David-Kress reconstruction on CPU and GPU, Parker short scan weighting, multi-threaded CPU and GPU forward projectors, etc. Each feature is either accessible through command line tools or C++ classes that can be included in independent software. A MIDAS community has been opened to share CatPhan datasets of several vendors (Elekta, Varian and IBA). RTK will be used in the upcoming cone-beam CT scanner developed by IBA for proton therapy rooms. Many features are under development: new input format support, iterative reconstruction, hybrid Monte Carlo / deterministic CBCT simulation, etc. RTK has been built to freely share tomographic reconstruction developments between researchers and is open for new contributions.

  4. FFT and cone-beam CT reconstruction on graphics hardware

    NASA Astrophysics Data System (ADS)

    Després, Philippe; Sun, Mingshan; Hasegawa, Bruce H.; Prevrhal, Sven

    2007-03-01

    Graphics processing units (GPUs) are increasingly used for general purpose calculations. Their pipelined architecture can be exploited to accelerate various parallelizable algorithms. Medical imaging applications are inherently well suited to benefit from the development of GPU-based computational platforms. We evaluate in this work the potential of GPUs to improve the execution speed of two common medical imaging tasks, namely Fourier transforms and tomographic reconstructions. A two-dimensional fast Fourier transform (FFT) algorithm was GPU-implemented and compared, in terms of execution speed, to two popular CPU-based FFT routines. Similarly, the Feldkamp, David and Kress (FDK) algorithm for cone-beam tomographic reconstruction was implemented on the GPU and its performance compared to a CPU version. Different reconstruction strategies were employed to assess the performance of various GPU memory layouts. For the specific hardware used, GPU implementations of the FFT were up to 20 times faster than their CPU counterparts, but slower than highly optimized CPU versions of the algorithm. Tomographic reconstructions were faster on the GPU by a factor up to 30, allowing 256 3 voxel reconstructions of 256 projections in about 20 seconds. Overall, GPUs are an attractive alternative to other imaging-dedicated computing hardware like application-specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs) in terms of cost, simplicity and versatility. With the development of simpler language extensions and programming interfaces, GPUs are likely to become essential tools in medical imaging.

  5. Multienergy CT acquisition and reconstruction with a stepped tube potential scan

    SciTech Connect

    Shen, Le; Xing, Yuxiang

    2015-01-15

    Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT can be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed Seg

  6. Three-dimensional cone-beam region-of-interest (ROI) CT reconstruction

    NASA Astrophysics Data System (ADS)

    Liu, Ruijie Rachel

    2001-06-01

    ROI cone-beam (CB) CT is proposed in this thesis as a new technique in which a set of partially filtered ROI images is used for CT reconstruction. It can be used in neural surgery as fluoroscopy 3D CT images with reduced dose outside the ROL Depending on the contrast resolution requirement of the CT images and therefore the thickness of the ROI filter, the dose can be reduced by 50%-70%. In this study, the shape of the ROI is rectangular in the middle of the image. In order to do CB reconstruction, the image distortion has to be corrected, because all the images were acquired by the image intensifier (II) where distortion occurs. We proposed a new method, named as super-global (SG) model with a set of parameters, to do distortion correction for all the images in a rotational run. The SG model is carefully tested and compared with the conventional global correction method Study shows that it is an accurate efficient method for the distortion correction of images acquired by rotational C-arms. The intensity of ROI images has to be equalized within and without ROI after distortion correction. First, the edge is detected; then equalization factors are applied to the filtered areas. Now the distortion-free and intensity-equalized images are used for CB backprojection to reconstruct the 3D CT images by Feldkamp algorithm. This algorithm is tested by a mathematical phantom reconstruction. Iso-center correction and uniform scattering subtraction is discussed and applied in the experimental phantom reconstruction. We took images of a phantom and a rabbit with and without contrast medium injection, and with and without ROI filtration. Their 3D CT images were obtained. For the rabbit, vascular CT images were obtained by subtracting CT images with contrast medium from those without contrast. The CT images of the ROI edges are in good shape, and no obvious artifact is observed. Though the filtered area has higher noise, its intensify is equalized pretty well with that of the

  7. Silk based bioinks for soft tissue reconstruction using 3-dimensional (3D) printing with in vitro and in vivo assessments.

    PubMed

    Rodriguez, María J; Brown, Joseph; Giordano, Jodie; Lin, Samuel J; Omenetto, Fiorenzo G; Kaplan, David L

    2017-02-01

    In the field of soft tissue reconstruction, custom implants could address the need for materials that can fill complex geometries. Our aim was to develop a material system with optimal rheology for material extrusion, that can be processed in physiological and non-toxic conditions and provide structural support for soft tissue reconstruction. To meet this need we developed silk based bioinks using gelatin as a bulking agent and glycerol as a non-toxic additive to induce physical crosslinking. We developed these inks optimizing printing efficacy and resolution for patient-specific geometries that can be used for soft tissue reconstruction. We demonstrated in vitro that the material was stable under physiological conditions and could be tuned to match soft tissue mechanical properties. We demonstrated in vivo that the material was biocompatible and could be tuned to maintain shape and volume up to three months while promoting cellular infiltration and tissue integration.

  8. CT x-ray tube voltage optimisation and image reconstruction evaluation using visual grading analysis

    NASA Astrophysics Data System (ADS)

    Zheng, Xiaoming; Kim, Ted M.; Davidson, Rob; Lee, Seongju; Shin, Cheongil; Yang, Sook

    2014-03-01

    The purposes of this work were to find an optimal x-ray voltage for CT imaging and to determine the diagnostic effectiveness of image reconstruction techniques by using the visual grading analysis (VGA). Images of the PH-5 CT abdomen phantom (Kagaku Co, Kyoto) were acquired by the Toshiba Aquillion One 320 slices CT system with various exposures (from 10 to 580 mAs) under different tube peak voltages (80, 100 and 120 kVp). The images were reconstructed by employing the FBP and the AIDR 3D iterative reconstructions with Mild, Standard and Strong FBP blending. Image quality was assessed by measuring noise, contrast to noise ratio and human observer's VGA scores. The CT dose index CTDIv was obtained from the values displayed on the images. The best fit for the curves of the image quality VGA vs dose CTDIv is a logistic function from the SPSS estimation. A threshold dose Dt is defined as the CTDIv at the just acceptable for diagnostic image quality and a figure of merit (FOM) is defined as the slope of the standardised logistic function. The Dt and FOM were found to be 5.4, 8.1 and 9.1 mGy and 0.47, 0.51 and 0.38 under the tube voltages of 80, 100 and 120 kVp, respectively, from images reconstructed by the FBP technique. The Dt and FOM values were lower from the images reconstructed by the AIDR 3D in comparison with the FBP technique. The optimal xray peak voltage for the imaging of the PH-5 abdomen phantom by the Aquillion One CT system was found to be at 100 kVp. The images reconstructed by the FBP are more diagnostically effective than that by the AIDR 3D but with a higher dose Dt to the patients.

  9. Micro-CT images reconstruction and 3D visualization for small animal studying

    NASA Astrophysics Data System (ADS)

    Gong, Hui; Liu, Qian; Zhong, Aijun; Ju, Shan; Fang, Quan; Fang, Zheng

    2005-01-01

    A small-animal x-ray micro computed tomography (micro-CT) system has been constructed to screen laboratory small animals and organs. The micro-CT system consists of dual fiber-optic taper-coupled CCD detectors with a field-of-view of 25x50 mm2, a microfocus x-ray source, a rotational subject holder. For accurate localization of rotation center, coincidence between the axis of rotation and centre of image was studied by calibration with a polymethylmethacrylate cylinder. Feldkamp"s filtered back-projection cone-beam algorithm is adopted for three-dimensional reconstruction on account of the effective corn-beam angle is 5.67° of the micro-CT system. 200x1024x1024 matrix data of micro-CT is obtained with the magnification of 1.77 and pixel size of 31x31μm2. In our reconstruction software, output image size of micro-CT slices data, magnification factor and rotation sample degree can be modified in the condition of different computational efficiency and reconstruction region. The reconstructed image matrix data is processed and visualization by Visualization Toolkit (VTK). Data parallelism of VTK is performed in surface rendering of reconstructed data in order to improve computing speed. Computing time of processing a 512x512x512 matrix datasets is about 1/20 compared with serial program when 30 CPU is used. The voxel size is 54x54x108 μm3. The reconstruction and 3-D visualization images of laboratory rat ear are presented.

  10. Alpha image reconstruction (AIR): A new iterative CT image reconstruction approach using voxel-wise alpha blending

    SciTech Connect

    Hofmann, Christian; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc

    2014-06-15

    factor for contrast-resolution plots. Furthermore, the authors calculate the contrast-to-noise ratio with the low contrast disks and the authors compare the agreement of the reconstructions with the ground truth by calculating the normalized cross-correlation and the root-mean-square deviation. To evaluate the clinical performance of the proposed method, the authors reconstruct patient data acquired with a Somatom Definition Flash dual source CT scanner (Siemens Healthcare, Forchheim, Germany). Results: The results of the simulation study show that among the compared algorithms AIR achieves the highest resolution and the highest agreement with the ground truth. Compared to the reference FBP reconstruction AIR is able to reduce the relative pixel noise by up to 50% and at the same time achieve a higher resolution by maintaining the edge information from the basis images. These results can be confirmed with the patient data. Conclusions: To evaluate the AIR algorithm simulated and measured patient data of a state-of-the-art clinical CT system were processed. It is shown, that generating CT images through the reconstruction of weighting coefficients has the potential to improve the resolution noise trade-off and thus to improve the dose usage in clinical CT.

  11. Extracting information from previous full-dose CT scan for knowledge-based Bayesian reconstruction of current low-dose CT images

    PubMed Central

    Zhang, Hao; Han, Hao; Liang, Zhengrong; Hu, Yifan; Liu, Yan; Moore, William; Ma, Jianhua; Lu, Hongbing

    2015-01-01

    Markov random field (MRF) model has been widely employed in edge-preserving regional noise smoothing penalty to reconstruct piece-wise smooth images in the presence of noise, such as in low-dose computed tomography (LdCT). While it preserves edge sharpness, its regional smoothing may sacrifice tissue image textures, which have been recognized as useful imaging biomarkers, and thus it may compromise clinical tasks such as differentiating malignant vs. benign lesions, e.g., lung nodules or colon polyps. This study aims to shift the edge-preserving regional noise smoothing paradigm to texture-preserving framework for LdCT image reconstruction while retaining the advantage of MRF’s neighborhood system on edge preservation. Specifically, we adapted the MRF model to incorporate the image textures of muscle, fat, bone, lung, etc. from previous full-dose CT (FdCT) scan as a priori knowledge for texture-preserving Bayesian reconstruction of current LdCT images. To show the feasibility of the proposed reconstruction framework, experiments using clinical patient scans were conducted. The experimental outcomes showed a dramatic gain by the a priori knowledge for LdCT image reconstruction using the commonly-used Haralick texture measures. Thus, it is conjectured that the texture-preserving LdCT reconstruction has advantages over the edge-preserving regional smoothing paradigm for texture-specific clinical applications. PMID:26561284

  12. Relaxed Linearized Algorithms for Faster X-Ray CT Image Reconstruction.

    PubMed

    Nien, Hung; Fessler, Jeffrey

    2015-12-17

    Statistical image reconstruction (SIR) methods are studied extensively for X-ray computed tomography (CT) due to the potential of acquiring CT scans with reduced X-ray dose while maintaining image quality. However, the longer reconstruction time of SIR methods hinders their use in X-ray CT in practice. To accelerate statistical methods, many optimization techniques have been investigated. Over-relaxation is a common technique to speed up convergence of iterative algorithms. For instance, using a relaxation parameter that is close to two in alternating direction method of multipliers (ADMM) has been shown to speed up convergence significantly. This paper proposes a relaxed linearized augmented Lagrangian (AL) method that shows theoretical faster convergence rate with over-relaxation and applies the proposed relaxed linearized AL method to X-ray CT image reconstruction problems. Experimental results with both simulated and real CT scan data show that the proposed relaxed algorithm (with ordered-subsets [OS] acceleration) is about twice as fast as the existing unrelaxed fast algorithms, with negligible computation and memory overhead.

  13. Relaxed Linearized Algorithms for Faster X-Ray CT Image Reconstruction.

    PubMed

    Nien, Hung; Fessler, Jeffrey A

    2016-04-01

    Statistical image reconstruction (SIR) methods are studied extensively for X-ray computed tomography (CT) due to the potential of acquiring CT scans with reduced X-ray dose while maintaining image quality. However, the longer reconstruction time of SIR methods hinders their use in X-ray CT in practice. To accelerate statistical methods, many optimization techniques have been investigated. Over-relaxation is a common technique to speed up convergence of iterative algorithms. For instance, using a relaxation parameter that is close to two in alternating direction method of multipliers (ADMM) has been shown to speed up convergence significantly. This paper proposes a relaxed linearized augmented Lagrangian (AL) method that shows theoretical faster convergence rate with over-relaxation and applies the proposed relaxed linearized AL method to X-ray CT image reconstruction problems. Experimental results with both simulated and real CT scan data show that the proposed relaxed algorithm (with ordered-subsets [OS] acceleration) is about twice as fast as the existing unrelaxed fast algorithms, with negligible computation and memory overhead.

  14. Minimizing image noise in on-board CT reconstruction using both kilovoltage and megavoltage beam projections.

    PubMed

    Zhang, Junan; Yin, Fang-Fang

    2007-09-01

    We studied a recently proposed aggregated CT reconstruction technique which combines the complementary advantages of kilovoltage (kV) and megavoltage (MV) x-ray imaging. Various phantoms were imaged to study the effects of beam orientations and geometry of the imaging object on image quality of reconstructed CT. It was shown that the quality of aggregated CT was correlated with both kV and MV beam orientations and the degree of this correlation depended upon the geometry of the imaging object. The results indicated that the optimal orientations were those when kV beams pass through the thinner portion and MV beams pass through the thicker portion of the imaging object. A special preprocessing procedure was also developed to perform contrast conversions between kV and MV information prior to image reconstruction. The performance of two reconstruction methods, one filtered backprojection method and one iterative method, were compared. The effects of projection number, beam truncation, and contrast conversion on the CT image quality were investigated.

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

    PubMed

    Zhang, Hao; Ma, Jianhua; Wang, Jing; Liu, Yan; Lu, Hongbing; Liang, Zhengrong

    2014-09-01

    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.

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

    PubMed Central

    Zhang, Hao; Ma, Jianhua; Wang, Jing; Liu, Yan; Lu, Hongbing

    2014-01-01

    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. PMID:24881498

  17. Role of CT Imaging with Volume Reconstruction in Hemi Facial Hypertrophy: A Pediatric Case Report.

    PubMed

    I, Gurubharath; Karanam, Lakshmi Sudha Prasanna; P, Ramesh

    2014-06-01

    Hemifacial hypertrophy is a rare congenital disorder more common in males.It involves the soft tissue, hard bones and teeth of the face.Its etiology is unknown and multiple theories have been postulated. We present a 6-year-old male with hemifacial hypertrophy and describes the importance of CT volume reconstruction in this condition.

  18. Filtered back-projection reconstruction for attenuation proton CT along most likely paths.

    PubMed

    Quiñones, C T; Létang, J M; Rit, S

    2016-05-07

    This work investigates the attenuation of a proton beam to reconstruct the map of the linear attenuation coefficient of a material which is mainly caused by the inelastic interactions of protons with matter. Attenuation proton computed tomography (pCT) suffers from a poor spatial resolution due to multiple Coulomb scattering (MCS) of protons in matter, similarly to the conventional energy-loss pCT. We therefore adapted a recent filtered back-projection algorithm along the most likely path (MLP) of protons for energy-loss pCT (Rit et al 2013) to attenuation pCT assuming a pCT scanner that can track the position and the direction of protons before and after the scanned object. Monte Carlo simulations of pCT acquisitions of density and spatial resolution phantoms were performed to characterize the new algorithm using Geant4 (via Gate). Attenuation pCT assumes an energy-independent inelastic cross-section, and the impact of the energy dependence of the inelastic cross-section below 100 MeV showed a capping artifact when the residual energy was below 100 MeV behind the object. The statistical limitation has been determined analytically and it was found that the noise in attenuation pCT images is 411 times and 278 times higher than the noise in energy-loss pCT images for the same imaging dose at 200 MeV and 300 MeV, respectively. Comparison of the spatial resolution of attenuation pCT images with a conventional straight-line path binning showed that incorporating the MLP estimates during reconstruction improves the spatial resolution of attenuation pCT. Moreover, regardless of the significant noise in attenuation pCT images, the spatial resolution of attenuation pCT was better than that of conventional energy-loss pCT in some studied situations thanks to the interplay of MCS and attenuation known as the West-Sherwood effect.

  19. Filtered back-projection reconstruction for attenuation proton CT along most likely paths

    NASA Astrophysics Data System (ADS)

    Quiñones, C. T.; Létang, J. M.; Rit, S.

    2016-05-01

    This work investigates the attenuation of a proton beam to reconstruct the map of the linear attenuation coefficient of a material which is mainly caused by the inelastic interactions of protons with matter. Attenuation proton computed tomography (pCT) suffers from a poor spatial resolution due to multiple Coulomb scattering (MCS) of protons in matter, similarly to the conventional energy-loss pCT. We therefore adapted a recent filtered back-projection algorithm along the most likely path (MLP) of protons for energy-loss pCT (Rit et al 2013) to attenuation pCT assuming a pCT scanner that can track the position and the direction of protons before and after the scanned object. Monte Carlo simulations of pCT acquisitions of density and spatial resolution phantoms were performed to characterize the new algorithm using Geant4 (via Gate). Attenuation pCT assumes an energy-independent inelastic cross-section, and the impact of the energy dependence of the inelastic cross-section below 100 MeV showed a capping artifact when the residual energy was below 100 MeV behind the object. The statistical limitation has been determined analytically and it was found that the noise in attenuation pCT images is 411 times and 278 times higher than the noise in energy-loss pCT images for the same imaging dose at 200 MeV and 300 MeV, respectively. Comparison of the spatial resolution of attenuation pCT images with a conventional straight-line path binning showed that incorporating the MLP estimates during reconstruction improves the spatial resolution of attenuation pCT. Moreover, regardless of the significant noise in attenuation pCT images, the spatial resolution of attenuation pCT was better than that of conventional energy-loss pCT in some studied situations thanks to the interplay of MCS and attenuation known as the West-Sherwood effect.

  20. TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT.

    PubMed

    Liu, Jiulong; Ding, Huanjun; Molloi, Sabee; Zhang, Xiaoqun; Gao, Hao

    2016-12-01

    This work develops a material reconstruction method for spectral CT, namely Total Image Constrained Material Reconstruction (TICMR), to maximize the utility of projection data in terms of both spectral information and high signal-to-noise ratio (SNR). This is motivated by the following fact: when viewed as a spectrally-integrated measurement, the projection data can be used to reconstruct a total image without spectral information, which however has a relatively high SNR; when viewed as a spectrally-resolved measurement, the projection data can be utilized to reconstruct the material composition, which however has a relatively low SNR. The material reconstruction synergizes material decomposition and image reconstruction, i.e., the direct reconstruction of material compositions instead of a two-step procedure that first reconstructs images and then decomposes images. For material reconstruction with high SNR, we propose TICMR with nonlocal total variation (NLTV) regularization. That is, first we reconstruct a total image using spectrally-integrated measurement without spectral binning, and build the NLTV weights from this image that characterize nonlocal image features; then the NLTV weights are incorporated into a NLTV-based iterative material reconstruction scheme using spectrally-binned projection data, so that these weights serve as a high-SNR reference to regularize material reconstruction. Note that the nonlocal property of NLTV is essential for material reconstruction, since material compositions may have significant local intensity variations although their structural information is often similar. In terms of solution algorithm, TICMR is formulated as an iterative reconstruction method with the NLTV regularization, in which the nonlocal divergence is utilized based on the adjoint relationship. The alternating direction method of multipliers is developed to solve this sparsity optimization problem. The proposed TICMR method was validated using both simulated

  1. SYRMEP Tomo Project: a graphical user interface for customizing CT reconstruction workflows.

    PubMed

    Brun, Francesco; Massimi, Lorenzo; Fratini, Michela; Dreossi, Diego; Billé, Fulvio; Accardo, Agostino; Pugliese, Roberto; Cedola, Alessia

    2017-01-01

    When considering the acquisition of experimental synchrotron radiation (SR) X-ray CT data, the reconstruction workflow cannot be limited to the essential computational steps of flat fielding and filtered back projection (FBP). More refined image processing is often required, usually to compensate artifacts and enhance the quality of the reconstructed images. In principle, it would be desirable to optimize the reconstruction workflow at the facility during the experiment (beamtime). However, several practical factors affect the image reconstruction part of the experiment and users are likely to conclude the beamtime with sub-optimal reconstructed images. Through an example of application, this article presents SYRMEP Tomo Project (STP), an open-source software tool conceived to let users design custom CT reconstruction workflows. STP has been designed for post-beamtime (off-line use) and for a new reconstruction of past archived data at user's home institution where simple computing resources are available. Releases of the software can be downloaded at the Elettra Scientific Computing group GitHub repository https://github.com/ElettraSciComp/STP-Gui.

  2. GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume

    PubMed Central

    Zhao, Xing; Hu, Jing-jing; Zhang, Peng

    2009-01-01

    Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs) has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation. PMID:19730744

  3. Reconstruction Algorithm with Improved Efficiency and Flexibility in Multi-Slice Spiral CT.

    PubMed

    Sun, Wenwu; Chen, Siping; Zhuang, Tiange

    2005-01-01

    There is a requirement for the development of CT to scan rapidly large longitudinal volume with high z-axis resolution. The combination of spiral scanning with multi-slice CT is a promising approach. The algorithm of image reconstruction for multi-slice spiral CT becomes, therefore, the main challenge. All algorithms known to the authors either need to derive the complementary data or work only for certain range of pitch values. This paper presents a novel reconstruction algorithm that can omit the derivations of the complementary data and work for arbitrary pitch values. The filter interpolation based on the proposed method is also easy to be implemented. The method is, thus, versatile. The results of computer simulations show that we can choose a combination of scan and filter parameters to meet the purpose of the examination.

  4. Spatial-temporal total variation regularization (STTVR) for 4D-CT reconstruction

    NASA Astrophysics Data System (ADS)

    Wu, Haibo; Maier, Andreas; Fahrig, Rebecca; Hornegger, Joachim

    2012-03-01

    Four dimensional computed tomography (4D-CT) is very important for treatment planning in thorax or abdomen area, e.g. for guiding radiation therapy planning. The respiratory motion makes the reconstruction problem illposed. Recently, compressed sensing theory was introduced. It uses sparsity as a prior to solve the problem and improves image quality considerably. However, the images at each phase are reconstructed individually. The correlations between neighboring phases are not considered in the reconstruction process. In this paper, we propose the spatial-temporal total variation regularization (STTVR) method which not only employs the sparsity in the spatial domain but also in the temporal domain. The algorithm is validated with XCAT thorax phantom. The Euclidean norm of the reconstructed image and ground truth is calculated for evaluation. The results indicate that our method improves the reconstruction quality by more than 50% compared to standard ART.

  5. Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners.

    PubMed

    Abella, M; Vaquero, J J; Sisniega, A; Pascau, J; Udías, A; García, V; Vidal, I; Desco, M

    2012-08-01

    Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. (FDK). Besides the implementation of the reconstruction algorithm itself, in order to design a real system it is necessary to take into account numerous issues so as to obtain the best quality images from the acquired data. This work presents a comprehensive, novel software architecture for small-animal CT scanners based on cone-beam geometry with circular scanning trajectory. The proposed architecture covers all the steps from the system calibration to the volume reconstruction and conversion into Hounsfield units. It includes an efficient implementation of an FDK-based reconstruction algorithm that takes advantage of system symmetries and allows for parallel reconstruction using a multiprocessor computer. Strategies for calibration and artifact correction are discussed to justify the strategies adopted. New procedures for multi-bed misalignment, beam-hardening, and Housfield units calibration are proposed. Experiments with phantoms and real data showed the suitability of the proposed software architecture for an X-ray small animal CT based on cone-beam geometry.

  6. An adaptive reconstruction algorithm for spectral CT regularized by a reference image

    NASA Astrophysics Data System (ADS)

    Wang, Miaoshi; Zhang, Yanbo; Liu, Rui; Guo, Shuxu; Yu, Hengyong

    2016-12-01

    The photon counting detector based spectral CT system is attracting increasing attention in the CT field. However, the spectral CT is still premature in terms of both hardware and software. To reconstruct high quality spectral images from low-dose projections, an adaptive image reconstruction algorithm is proposed that assumes a known reference image (RI). The idea is motivated by the fact that the reconstructed images from different spectral channels are highly correlated. If a high quality image of the same object is known, it can be used to improve the low-dose reconstruction of each individual channel. This is implemented by maximizing the patch-wise correlation between the object image and the RI. Extensive numerical simulations and preclinical mouse study demonstrate the feasibility and merits of the proposed algorithm. It also performs well for truncated local projections, and the surrounding area of the region- of-interest (ROI) can be more accurately reconstructed. Furthermore, a method is introduced to adaptively choose the step length, making the algorithm more feasible and easier for applications.

  7. Low-dose X-ray CT reconstruction via dictionary learning.

    PubMed

    Xu, Qiong; Yu, Hengyong; Mou, Xuanqin; Zhang, Lei; Hsieh, Jiang; Wang, Ge

    2012-09-01

    Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures.

  8. Reconstruction of 4D-CT from a Single Free-Breathing 3D-CT by Spatial-Temporal Image Registration

    PubMed Central

    Wu, Guorong; Wang, Qian; Lian, Jun; Shen, Dinggang

    2011-01-01

    In the radiation therapy of lung cancer, a free-breathing 3D-CT image is usually acquired in the treatment day for image-guided patient setup, by registering with the free-breathing 3D-CT image acquired in the planning day. In this way, the optimal dose plan computed in the planning day can be transferred onto the treatment day for cancer radiotherapy. However, patient setup based on the simple registration of the free-breathing 3D-CT images of the planning and the treatment days may mislead the radiotherapy, since the free-breathing 3D-CT is actually the mixed-phase image, with different slices often acquired from different respiratory phases. Moreover, a 4D-CT that is generally acquired in the planning day for improvement of dose planning is often ignored for guiding patient setup in the treatment day. To overcome these limitations, we present a novel two-step method to reconstruct the 4D-CT from a single free-breathing 3D-CT of the treatment day, by utilizing the 4D-CT model built in the planning day. Specifically, in the first step, we proposed a new spatial-temporal registration algorithm to align all phase images of the 4D-CT acquired in the planning day, for building a 4D-CT model with temporal correspondences established among all respiratory phases. In the second step, we first determine the optimal phase for each slice of the free-breathing (mixed-phase) 3D-CT of the treatment day by comparing with the 4D-CT of the planning day and thus obtain a sequence of partial 3D-CT images for the treatment day, each with only the incomplete image information in certain slices; and then we reconstruct a complete 4D-CT for the treatment day by warping the 4D-CT of the planning day (with complete information) to the sequence of partial 3D-CT images of the treatment day, under the guidance of the 4D-CT model built in the planning day. We have comprehensively evaluated our 4D-CT model building algorithm on a public lung image database, achieving the best registration

  9. Rank-sparsity constrained, spectro-temporal reconstruction for retrospectively gated, dynamic CT

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Lee, C. L.; Kirsch, D. G.; Badea, C. T.

    2015-03-01

    Relative to prospective projection gating, retrospective projection gating for dynamic CT applications allows fast imaging times, minimizing the potential for physiological and anatomic variability. Preclinically, fast imaging is attractive due to the rapid clearance of low molecular weight contrast agents and the rapid heart rate of rodents. Clinically, retrospective gating is relevant for intraoperative C-arm CT. More generally, retrospective sampling provides an opportunity for significant reduction in x-ray dose within the framework of compressive sensing theory and sparsity-constrained iterative reconstruction. Even so, CT reconstruction from projections with random temporal sampling is a very poorly conditioned inverse problem, requiring high fidelity regularization to minimize variability in the reconstructed results. Here, we introduce a highly novel data acquisition and regularization strategy for spectro-temporal (5D) CT reconstruction from retrospectively gated projections. We show that by taking advantage of the rank-sparse structure and separability of the temporal and spectral reconstruction sub-problems, being able to solve each sub-problem independently effectively guarantees that we can solve both problems together. In this paper, we show 4D simulation results (2D + 2 energies + time) using the proposed technique and compare them with two competing techniques— spatio-temporal total variation minimization and prior image constrained compressed sensing. We also show in vivo, 5D (3D + 2 energies + time) myocardial injury data acquired in a mouse, reconstructing 20 data sets (10 phases, 2 energies) and performing material decomposition from data acquired over a single rotation (360°, dose: ~60 mGy).

  10. Smoothed l0 Norm Regularization for Sparse-View X-Ray CT Reconstruction

    PubMed Central

    Li, Ming; Peng, Chengtao; Guan, Yihui; Xu, Pin

    2016-01-01

    Low-dose computed tomography (CT) reconstruction is a challenging problem in medical imaging. To complement the standard filtered back-projection (FBP) reconstruction, sparse regularization reconstruction gains more and more research attention, as it promises to reduce radiation dose, suppress artifacts, and improve noise properties. In this work, we present an iterative reconstruction approach using improved smoothed l0 (SL0) norm regularization which is used to approximate l0 norm by a family of continuous functions to fully exploit the sparseness of the image gradient. Due to the excellent sparse representation of the reconstruction signal, the desired tissue details are preserved in the resulting images. To evaluate the performance of the proposed SL0 regularization method, we reconstruct the simulated dataset acquired from the Shepp-Logan phantom and clinical head slice image. Additional experimental verification is also performed with two real datasets from scanned animal experiment. Compared to the referenced FBP reconstruction and the total variation (TV) regularization reconstruction, the results clearly reveal that the presented method has characteristic strengths. In particular, it improves reconstruction quality via reducing noise while preserving anatomical features. PMID:27725935

  11. Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

    SciTech Connect

    Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

    2013-11-15

    Purpose: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables.Methods: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision.Results: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A.Conclusions: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of

  12. Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning

    SciTech Connect

    Yin, Zhye De Man, Bruno; Yao, Yangyang; Wu, Mingye; Montillo, Albert; Edic, Peter M.; Kalra, Mannudeep

    2015-05-15

    Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies to achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.

  13. An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion

    SciTech Connect

    Lin, Yuan Samei, Ehsan

    2014-02-15

    Purpose: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. Methods: Our algorithm made threea priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. Results: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced

  14. Pixel-based reconstruction (PBR) promising simultaneous techniques for CT reconstructions.

    PubMed

    Fager, R S; Peddanarappagari, K V; Kumar, G N

    1993-01-01

    Algorithms belonging to the class of pixel-based reconstruction (PBR) algorithms, which are similar to simultaneous iterative reconstruction techniques (SIRTs) for reconstruction of objects from their fan beam projections in X-ray transmission tomography, are discussed. The general logic of these algorithms is discussed. Simulation studies indicate that, contrary to previous results with parallel beam projections, the iterative algebraic algorithms do not diverge when a more logical technique of obtaining the pseudoprojections is used. These simulations were carried out under conditions in which the number of object pixels exceeded (double) the number of detector pixel readings, i.e., the equations were highly underdetermined. The effect of the number of projections on the reconstruction and the convergence (empirical) to the exact solution is shown. For comparison, the reconstructions obtained by convolution backprojection are also given.

  15. A motion-compensated scheme for helical cone-beam reconstruction in cardiac CT angiography

    SciTech Connect

    Stevendaal, U. van; Berg, J. von; Lorenz, C.; Grass, M.

    2008-07-15

    Since coronary heart disease is one of the main causes of death all over the world, cardiac computed tomography (CT) imaging is an application of very high interest in order to verify indications timely. Due to the cardiac motion, electrocardiogram (ECG) gating has to be implemented into the reconstruction of the measured projection data. However, the temporal and spatial resolution is limited due to the mechanical movement of the gantry and due to the fact that a finite angular span of projections has to be acquired for the reconstruction of each voxel. In this article, a motion-compensated reconstruction method for cardiac CT is described, which can be used to increase the signal-to-noise ratio or to suppress motion blurring. Alternatively, it can be translated into an improvement of the temporal and spatial resolution. It can be applied to the entire heart in common and to high contrast objects moving with the heart in particular, such as calcified plaques or devices like stents. The method is based on three subsequent steps: As a first step, the projection data acquired in low pitch helical acquisition mode together with the ECG are reconstructed at multiple phase points. As a second step, the motion-vector field is calculated from the reconstructed images in relation to the image in a reference phase. Finally, a motion-compensated reconstruction is carried out for the reference phase using those projections, which cover the cardiac phases for which the motion-vector field has been determined.

  16. Normalization of CT scans reconstructed with different kernels to reduce variability in emphysema measurements

    NASA Astrophysics Data System (ADS)

    Gallardo Estrella, L.; van Ginneken, B.; van Rikxoort, E. M.

    2013-03-01

    Chronic Obstructive Pulmonary Disease (COPD) is a lung disease characterized by progressive air flow limitation caused by emphysema and chronic bronchitis. Emphysema is quantified from chest computed tomography (CT) scans as the percentage of attentuation values below a fixed threshold. The emphysema quantification varies substantially between scans reconstructed with different kernels, limiting the possibilities to compare emphysema quantifications obtained from scans with different reconstruction parameters. In this paper we propose a method to normalize scans reconstructed with different kernels to have the same characteristics as scans reconstructed with a reference kernel and investigate if this normalization reduces the variability in emphysema quantification. The proposed normalization splits a CT scan into different frequency bands based on hierarchical unsharp masking. Normalization is performed by changing the energy in each frequency band to the average energy in each band in the reference kernel. A database of 15 subjects with COPD was constructed for this study. All subjects were scanned at total lung capacity and the scans were reconstructed with four different reconstruction kernels. The normalization was applied to all scans. Emphysema quantification was performed before and after normalization. It is shown that the emphysema score varies substantially before normalization but the variation diminishes after normalization.

  17. Phase-selective image reconstruction of the lungs in small animals using micro-CT

    NASA Astrophysics Data System (ADS)

    Johnston, S. M.; Perez, B. A.; Kirsch, D. G.; Badea, C. T.

    2010-04-01

    Gating in small animal imaging can compensate for artifacts due to physiological motion. This paper presents a strategy for sampling and image reconstruction in the rodent lung using micro-CT. The approach involves rapid sampling of freebreathing mice without any additional hardware to detect respiratory motion. The projection images are analyzed postacquisition to derive a respiratory signal, which is used to provide weighting factors for each projection that favor a selected phase of the respiration (e.g. end-inspiration or end-expiration) for the reconstruction. Since the sampling cycle and the respiratory cycle are uncorrelated, the sets of projections corresponding to any of the selected respiratory phases do not have a regular angular distribution. This drastically affects the image quality of reconstructions based on simple filtered backprojection. To address this problem, we use an iterative reconstruction algorithm that combines the Simultaneous Algebraic Reconstruction Technique with Total Variation minimization (SART-TV). At each SART-TV iteration, backprojection is performed with a set of weighting factors that favor the desired respiratory phase. To reduce reconstruction time, the algorithm is implemented on a graphics processing unit. The performance of the proposed approach was investigated in simulations and in vivo scans of mice with primary lung cancers imaged with our in-house developed dual tube/detector micro-CT system. We note that if the ECG signal is acquired during sampling, the same approach could be used for phase-selective cardiac imaging.

  18. PET/CT (and CT) instrumentation, image reconstruction and data transfer for radiotherapy planning.

    PubMed

    Sattler, Bernhard; Lee, John A; Lonsdale, Markus; Coche, Emmanuel

    2010-09-01

    The positron emission tomography in combination with CT in hybrid, cross-modality imaging systems (PET/CT) gains more and more importance as a part of the treatment-planning procedure in radiotherapy. Positron emission tomography (PET), as a integral part of nuclear medicine imaging and non-invasive imaging technique, offers the visualization and quantification of pre-selected tracer metabolism. In combination with the structural information from CT, this molecular imaging technique has great potential to support and improve the outcome of the treatment-planning procedure prior to radiotherapy. By the choice of the PET-Tracer, a variety of different metabolic processes can be visualized. First and foremost, this is the glucose metabolism of a tissue as well as for instance hypoxia or cell proliferation. This paper comprises the system characteristics of hybrid PET/CT systems. Acquisition and processing protocols are described in general and modifications to cope with the special needs in radiooncology. This starts with the different position of the patient on a special table top, continues with the use of the same fixation material as used for positioning of the patient in radiooncology while simulation and irradiation and leads to special processing protocols that include the delineation of the volumes that are subject to treatment planning and irradiation (PTV, GTV, CTV, etc.). General CT acquisition and processing parameters as well as the use of contrast enhancement of the CT are described. The possible risks and pitfalls the investigator could face during the hybrid-imaging procedure are explained and listed. The interdisciplinary use of different imaging modalities implies a increase of the volume of data created. These data need to be stored and communicated fast, safe and correct. Therefore, the DICOM-Standard provides objects and classes for this purpose (DICOM RT). Furthermore, the standard DICOM objects and classes for nuclear medicine (NM, PT) and

  19. Endoscopic-CT: learning-based photometric reconstruction for endoscopic sinus surgery

    NASA Astrophysics Data System (ADS)

    Reiter, A.; Leonard, S.; Sinha, A.; Ishii, M.; Taylor, R. H.; Hager, G. D.

    2016-03-01

    In this work we present a method for dense reconstruction of anatomical structures using white light endoscopic imagery based on a learning process that estimates a mapping between light reflectance and surface geometry. Our method is unique in that few unrealistic assumptions are considered (i.e., we do not assume a Lambertian reflectance model nor do we assume a point light source) and we learn a model on a per-patient basis, thus increasing the accuracy and extensibility to different endoscopic sequences. The proposed method assumes accurate video-CT registration through a combination of Structure-from-Motion (SfM) and Trimmed-ICP, and then uses the registered 3D structure and motion to generate training data with which to learn a multivariate regression of observed pixel values to known 3D surface geometry. We demonstrate with a non-linear regression technique using a neural network towards estimating depth images and surface normal maps, resulting in high-resolution spatial 3D reconstructions to an average error of 0.53mm (on the low side, when anatomy matches the CT precisely) to 1.12mm (on the high side, when the presence of liquids causes scene geometry that is not present in the CT for evaluation). Our results are exhibited on patient data and validated with associated CT scans. In total, we processed 206 total endoscopic images from patient data, where each image yields approximately 1 million reconstructed 3D points per image.

  20. Effect of low-dose CT and iterative reconstruction on trabecular bone microstructure assessment

    NASA Astrophysics Data System (ADS)

    Kopp, Felix K.; Baum, Thomas; Nasirudin, Radin A.; Mei, Kai; Garcia, Eduardo G.; Burgkart, Rainer; Rummeny, Ernst J.; Bauer, Jan S.; Noël, Peter B.

    2016-03-01

    The trabecular bone microstructure is an important factor in the development of osteoporosis. It is well known that its deterioration is one effect when osteoporosis occurs. Previous research showed that the analysis of trabecular bone microstructure enables more precise diagnoses of osteoporosis compared to a sole measurement of the mineral density. Microstructure parameters are assessed on volumetric images of the bone acquired either with high-resolution magnetic resonance imaging, high-resolution peripheral quantitative computed tomography or high-resolution computed tomography (CT), with only CT being applicable to the spine, which is one of clinically most relevant fracture sites. However, due to the high radiation exposure for imaging the whole spine these measurements are not applicable in current clinical routine. In this work, twelve vertebrae from three different donors were scanned with standard and low radiation dose. Trabecular bone microstructure parameters were assessed for CT images reconstructed with statistical iterative reconstruction (SIR) and analytical filtered backprojection (FBP). The resulting structure parameters were correlated to the biomechanically determined fracture load of each vertebra. Microstructure parameters assessed for low-dose data reconstructed with SIR significantly correlated with fracture loads as well as parameters assessed for standard-dose data reconstructed with FBP. Ideal results were achieved with low to zero regularization strength yielding microstructure parameters not significantly different from those assessed for standard-dose FPB data. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

  1. A multi-resolution approach to retrospectively-gated cardiac micro-CT reconstruction

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Johnson, G. A.; Badea, C. T.

    2014-03-01

    In preclinical research, micro-CT is commonly used to provide anatomical information; however, there is significant interest in using this technology to obtain functional information in cardiac studies. The fastest acquisition in 4D cardiac micro-CT imaging is achieved via retrospective gating, resulting in irregular angular projections after binning the projections into phases of the cardiac cycle. Under these conditions, analytical reconstruction algorithms, such as filtered back projection, suffer from streaking artifacts. Here, we propose a novel, multi-resolution, iterative reconstruction algorithm inspired by robust principal component analysis which prevents the introduction of streaking artifacts, while attempting to recover the highest temporal resolution supported by the projection data. The algorithm achieves these results through a unique combination of the split Bregman method and joint bilateral filtration. We illustrate the algorithm's performance using a contrast-enhanced, 2D slice through the MOBY mouse phantom and realistic projection acquisition and reconstruction parameters. Our results indicate that the algorithm is robust to under sampling levels of only 34 projections per cardiac phase and, therefore, has high potential in reducing both acquisition times and radiation dose. Another potential advantage of the multi-resolution scheme is the natural division of the reconstruction problem into a large number of independent sub-problems which can be solved in parallel. In future work, we will investigate the performance of this algorithm with retrospectively-gated, cardiac micro-CT data.

  2. GPU-accelerated regularized iterative reconstruction for few-view cone beam CT

    SciTech Connect

    Matenine, Dmitri; Goussard, Yves

    2015-04-15

    Purpose: The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames. Methods: The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it is implemented on a graphics processing unit, using parallelization to accelerate computations. Results: The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1–2 min and are compatible with the typical clinical workflow for nonreal-time applications. Conclusions: Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.

  3. Novel iterative reconstruction method with optimal dose usage for partially redundant CT-acquisition

    NASA Astrophysics Data System (ADS)

    Bruder, H.; Raupach, R.; Sunnegardh, J.; Allmendinger, T.; Klotz, E.; Stierstorfer, K.; Flohr, T.

    2015-11-01

    In CT imaging, a variety of applications exist which are strongly SNR limited. However, in some cases redundant data of the same body region provide additional quanta. Examples: in dual energy CT, the spatial resolution has to be compromised to provide good SNR for material decomposition. However, the respective spectral dataset of the same body region provides additional quanta which might be utilized to improve SNR of each spectral component. Perfusion CT is a high dose application, and dose reduction is highly desirable. However, a meaningful evaluation of perfusion parameters might be impaired by noisy time frames. On the other hand, the SNR of the average of all time frames is extremely high. In redundant CT acquisitions, multiple image datasets can be reconstructed and averaged to composite image data. These composite image data, however, might be compromised with respect to contrast resolution and/or spatial resolution and/or temporal resolution. These observations bring us to the idea of transferring high SNR of composite image data to low SNR ‘source’ image data, while maintaining their resolution. It has been shown that the noise characteristics of CT image data can be improved by iterative reconstruction (Popescu et al 2012 Book of Abstracts, 2nd CT Meeting (Salt Lake City, UT) p 148). In case of data dependent Gaussian noise it can be modelled with image-based iterative reconstruction at least in an approximate manner (Bruder et al 2011 Proc. SPIE 7961 79610J). We present a generalized update equation in image space, consisting of a linear combination of the previous update, a correction term which is constrained by the source image data, and a regularization prior, which is initialized by the composite image data. This iterative reconstruction approach we call bimodal reconstruction (BMR). Based on simulation data it is shown that BMR can improve low contrast detectability, substantially reduces the noise power and has the potential to recover

  4. Novel iterative reconstruction method with optimal dose usage for partially redundant CT-acquisition.

    PubMed

    Bruder, H; Raupach, R; Sunnegardh, J; Allmendinger, T; Klotz, E; Stierstorfer, K; Flohr, T

    2015-11-07

    In CT imaging, a variety of applications exist which are strongly SNR limited. However, in some cases redundant data of the same body region provide additional quanta. Examples in dual energy CT, the spatial resolution has to be compromised to provide good SNR for material decomposition. However, the respective spectral dataset of the same body region provides additional quanta which might be utilized to improve SNR of each spectral component. Perfusion CT is a high dose application, and dose reduction is highly desirable. However, a meaningful evaluation of perfusion parameters might be impaired by noisy time frames. On the other hand, the SNR of the average of all time frames is extremely high.In redundant CT acquisitions, multiple image datasets can be reconstructed and averaged to composite image data. These composite image data, however, might be compromised with respect to contrast resolution and/or spatial resolution and/or temporal resolution. These observations bring us to the idea of transferring high SNR of composite image data to low SNR 'source' image data, while maintaining their resolution.It has been shown that the noise characteristics of CT image data can be improved by iterative reconstruction (Popescu et al 2012 Book of Abstracts, 2nd CT Meeting (Salt Lake City, UT) p 148). In case of data dependent Gaussian noise it can be modelled with image-based iterative reconstruction at least in an approximate manner (Bruder et al 2011 Proc. SPIE 7961 79610J). We present a generalized update equation in image space, consisting of a linear combination of the previous update, a correction term which is constrained by the source image data, and a regularization prior, which is initialized by the composite image data. This iterative reconstruction approach we call bimodal reconstruction (BMR). Based on simulation data it is shown that BMR can improve low contrast detectability, substantially reduces the noise power and has the potential to recover spatial

  5. "High-precision, reconstructed 3D model" of skull scanned by conebeam CT: Reproducibility verified using CAD/CAM data.

    PubMed

    Katsumura, Seiko; Sato, Keita; Ikawa, Tomoko; Yamamura, Keiko; Ando, Eriko; Shigeta, Yuko; Ogawa, Takumi

    2016-01-01

    Computed tomography (CT) scanning has recently been introduced into forensic medicine and dentistry. However, the presence of metal restorations in the dentition can adversely affect the quality of three-dimensional reconstruction from CT scans. In this study, we aimed to evaluate the reproducibility of a "high-precision, reconstructed 3D model" obtained from a conebeam CT scan of dentition, a method that might be particularly helpful in forensic medicine. We took conebeam CT and helical CT images of three dry skulls marked with 47 measuring points; reconstructed three-dimensional images; and measured the distances between the points in the 3D images with a computer-aided design/computer-aided manufacturing (CAD/CAM) marker. We found that in comparison with the helical CT, conebeam CT is capable of reproducing measurements closer to those obtained from the actual samples. In conclusion, our study indicated that the image-reproduction from a conebeam CT scan was more accurate than that from a helical CT scan. Furthermore, the "high-precision reconstructed 3D model" facilitates reliable visualization of full-sized oral and maxillofacial regions in both helical and conebeam CT scans.

  6. Surgical anatomy of the frontal recess--is there a benefit in multiplanar CT-reconstruction?

    PubMed

    Leunig, A; Sommer, B; Betz, C S; Sommer, F

    2008-09-01

    Anatomical variations in the sinus region are not necessarily pathological, but they may complicate the anatomy of the lateral nasal wall and contribute to the occurrence or persistence of chronic inflammatory diseases. In this study the interpretations of initial coronal CT scans were significantly altered following multiplanar CT-reconstruction. Assuming that a multiplanar analysis includes coronal views, we may conclude that imaging in three planes yields more information and provides a substantial benefit in the planning and performance of a surgical procedure on the paranasal sinuses.

  7. Performance analysis of model based iterative reconstruction with dictionary learning in transportation security CT

    NASA Astrophysics Data System (ADS)

    Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno

    2016-05-01

    In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.

  8. Evaluation of accuracy of 3D reconstruction images using multi-detector CT and cone-beam CT

    PubMed Central

    Kim, Mija; YI, Won-Jin; Heo, Min-Suk; Lee, Sam-Sun; Choi, Soon-Chul

    2012-01-01

    Purpose This study was performed to determine the accuracy of linear measurements on three-dimensional (3D) images using multi-detector computed tomography (MDCT) and cone-beam computed tomography (CBCT). Materials and Methods MDCT and CBCT were performed using 24 dry skulls. Twenty-one measurements were taken on the dry skulls using digital caliper. Both types of CT data were imported into OnDemand software and identification of landmarks on the 3D surface rendering images and calculation of linear measurements were performed. Reproducibility of the measurements was assessed using repeated measures ANOVA and ICC, and the measurements were statistically compared using a Student t-test. Results All assessments under the direct measurement and image-based measurements on the 3D CT surface rendering images using MDCT and CBCT showed no statistically difference under the ICC examination. The measurements showed no differences between the direct measurements of dry skull and the image-based measurements on the 3D CT surface rendering images (P>.05). Conclusion Three-dimensional reconstructed surface rendering images using MDCT and CBCT would be appropriate for 3D measurements. PMID:22474645

  9. On proton CT reconstruction using MVCT-converted virtual proton projections

    SciTech Connect

    Wang Dongxu; Mackie, T. Rockwell; Tome, Wolfgang A.

    2012-06-15

    Purpose: To describe a novel methodology of converting megavoltage x-ray projections into virtual proton projections that are otherwise missing due to the proton range limit. These converted virtual proton projections can be used in the reconstruction of proton computed tomography (pCT). Methods: Relations exist between proton projections and multispectral megavoltage x-ray projections for human tissue. Based on these relations, these tissues can be categorized into: (a) adipose tissue; (b) nonadipose soft tissues; and (c) bone. These three tissue categories can be visibly identified on a regular megavoltage x-ray computed tomography (MVCT) image. With an MVCT image and its projection data available, the x-ray projections through heterogeneous anatomy can be converted to the corresponding proton projections using predetermined calibration curves for individual materials, aided by a coarse segmentation on the x-ray CT image. To show the feasibility of this approach, mathematical simulations were carried out. The converted proton projections, plotted on a proton sinogram, were compared to the simulated ground truth. Proton stopping power images were reconstructed using either the virtual proton projections only or a blend of physically available proton projections and virtual proton projections that make up for those missing due to the range limit. These images were compared to a reference image reconstructed from theoretically calculated proton projections. Results: The converted virtual projections had an uncertainty of {+-}0.8% compared to the calculated ground truth. Proton stopping power images reconstructed using a blend of converted virtual projections (48%) and physically available projections (52%) had an uncertainty of {+-}0.86% compared with that reconstructed from theoretically calculated projections. Reconstruction solely from converted virtual proton projections had an uncertainty of {+-}1.1% compared with that reconstructed from theoretical projections

  10. Projection domain denoising method based on dictionary learning for low-dose CT image reconstruction.

    PubMed

    Zhang, Haiyan; Zhang, Liyi; Sun, Yunshan; Zhang, Jingyu

    2015-01-01

    Reducing X-ray tube current is one of the widely used methods for decreasing the radiation dose. Unfortunately, the signal-to-noise ratio (SNR) of the projection data degrades simultaneously. To improve the quality of reconstructed images, a dictionary learning based penalized weighted least-squares (PWLS) approach is proposed for sinogram denoising. The weighted least-squares considers the statistical characteristic of noise and the penalty models the sparsity of sinogram based on dictionary learning. Then reconstruct CT image using filtered back projection (FBP) algorithm from the denoised sinogram. The proposed method is particularly suitable for the projection data with low SNR. Experimental results show that the proposed method can get high-quality CT images when the signal to noise ratio of projection data declines sharply.

  11. Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET

    NASA Astrophysics Data System (ADS)

    Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E.; Nuyts, Johan

    2016-02-01

    Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov’s momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

  12. Imaging detection of new HCCs in cirrhotic patients treated with different techniques: Comparison of conventional US, spiral CT, and 3-dimensional contrast-enhanced US with the Navigator technique (Nav 3D CEUS)☆

    PubMed Central

    Giangregorio, F.; Comparato, G.; Marinone, M.G.; Di Stasi, M.; Sbolli, G.; Aragona, G.; Tansini, P.; Fornari, F.

    2009-01-01

    Introduction The commercially available Navigator system© (Esaote, Italy) allows easy 3D reconstruction of a single 2D acquisition of contrast-enhanced US (CEUS) imaging of the whole liver (with volumetric correction provided by the electromagnetic device of the Navigator©). The aim of our study was to compare the efficacy of this panoramic technique (Nav 3D CEUS) with that of conventional US and spiral CT in the detection of new hepatic lesions in patients treated for hepatocellular carcinoma (HCC). Materials and methods From November 2006 to May 2007, we performed conventional US, Nav 3D CEUS, and spiral CT on 72 cirrhotic patients previously treated for 1 or more HCCs (M/F: 38/34; all HCV-positive; Child: A/B 58/14) (1 examination: 48 patients; 2 examinations: 20 patients; 3 examinations: 4 patients). Nav 3D CEUS was performed with SonoVue© (Bracco, Milan, Italy) as a contrast agent and Technos MPX© scanner (Esaote, Genoa, Italy). Sensitivity, specificity, diagnostic accuracy, and positive and negative predictive values (PPV and NPV, respectively) were evaluated. Differences between the techniques were assessed with the chi-square test (SPSS release-15). Results Definitive diagnoses (based on spiral CT and additional follow-up) were: 6 cases of local recurrence (LocRecs) in 4 patients, 49 new nodules >2 cm from a treated nodule (NewNods) in 34 patients, and 10 cases of multinodular recurrence consisting of 4 or more nodules (NewMulti). The remaining 24 patients (22 treated for 1–3 nodules, 2 treated for >3 nodules) remained recurrence-free. Conventional US correctly detected 29/49 NewNods, 9/10 NewMultis, and 3/6 LocRecs (sensitivity: 59.2%; specificity: 100%; diagnostic accuracy: 73.6%; PPV: 100%; NPV: 70.1%). Spiral CT detected 42/49 NewNods plus 1 that was a false positive, 9/10 NewMultis, and all 6 LocRecs (sensitivity: 85.7%; specificity: 95.7%; diagnostic accuracy: 90.9%; PPV: 97.7%; NPV: 75.9%). 3D NAV results were: 46N (+9 multinodularN and 6 LR

  13. Objective assessment of image quality and dose reduction in CT iterative reconstruction

    SciTech Connect

    Vaishnav, J. Y. Jung, W. C.; Popescu, L. M.; Zeng, R.; Myers, K. J.

    2014-07-15

    Purpose: Iterative reconstruction (IR) algorithms have the potential to reduce radiation dose in CT diagnostic imaging. As these algorithms become available on the market, a standardizable method of quantifying the dose reduction that a particular IR method can achieve would be valuable. Such a method would assist manufacturers in making promotional claims about dose reduction, buyers in comparing different devices, physicists in independently validating the claims, and the United States Food and Drug Administration in regulating the labeling of CT devices. However, the nonlinear nature of commercially available IR algorithms poses challenges to objectively assessing image quality, a necessary step in establishing the amount of dose reduction that a given IR algorithm can achieve without compromising that image quality. This review paper seeks to consolidate information relevant to objectively assessing the quality of CT IR images, and thereby measuring the level of dose reduction that a given IR algorithm can achieve. Methods: The authors discuss task-based methods for assessing the quality of CT IR images and evaluating dose reduction. Results: The authors explain and review recent literature on signal detection and localization tasks in CT IR image quality assessment, the design of an appropriate phantom for these tasks, possible choices of observers (including human and model observers), and methods of evaluating observer performance. Conclusions: Standardizing the measurement of dose reduction is a problem of broad interest to the CT community and to public health. A necessary step in the process is the objective assessment of CT image quality, for which various task-based methods may be suitable. This paper attempts to consolidate recent literature that is relevant to the development and implementation of task-based methods for the assessment of CT IR image quality.

  14. Adapted morphing model for 3D volume reconstruction applied to abdominal CT images

    NASA Astrophysics Data System (ADS)

    Fadeev, Aleksey; Eltonsy, Nevine; Tourassi, Georgia; Martin, Robert; Elmaghraby, Adel

    2005-04-01

    The purpose of this study was to develop a 3D volume reconstruction model for volume rendering and apply this model to abdominal CT data. The model development includes two steps: (1) interpolation of given data for a complete 3D model, and (2) visualization. First, CT slices are interpolated using a special morphing algorithm. The main idea of this algorithm is to take a region from one CT slice and locate its most probable correspondence in the adjacent CT slice. The algorithm determines the transformation function of the region in between two adjacent CT slices and interpolates the data accordingly. The most probable correspondence of a region is obtained using correlation analysis between the given region and regions of the adjacent CT slice. By applying this technique recursively, taking progressively smaller subregions within a region, a high quality and accuracy interpolation is obtained. The main advantages of this morphing algorithm are 1) its applicability not only to parallel planes like CT slices but also to general configurations of planes in 3D space, and 2) its fully automated nature as it does not require control points to be specified by a user compared to most morphing techniques. Subsequently, to visualize data, a specialized volume rendering card (TeraRecon VolumePro 1000) was used. To represent data in 3D space, special software was developed to convert interpolated CT slices to 3D objects compatible with the VolumePro card. Visual comparison between the proposed model and linear interpolation clearly demonstrates the superiority of the proposed model.

  15. 3D cardiac motion reconstruction from CT data and tagged MRI.

    PubMed

    Wang, Xiaoxu; Mihalef, Viorel; Qian, Zhen; Voros, Szilard; Metaxas, Dimitris

    2012-01-01

    In this paper we present a novel method for left ventricle (LV) endocardium motion reconstruction using high resolution CT data and tagged MRI. High resolution CT data provide anatomic details on the LV endocardial surface, such as the papillary muscle and trabeculae carneae. Tagged MRI provides better time resolution. The combination of these two imaging techniques can give us better understanding on left ventricle motion. The high resolution CT images are segmented with mean shift method and generate the LV endocardium mesh. The meshless deformable model built with high resolution endocardium surface from CT data fit to the tagged MRI of the same phase. 3D deformation of the myocardium is computed with the Lagrangian dynamics and local Laplacian deformation. The segmented inner surface of left ventricle is compared with the heart inner surface picture and show high agreement. The papillary muscles are attached to the inner surface with roots. The free wall of the left ventricle inner surface is covered with trabeculae carneae. The deformation of the heart wall and the papillary muscle in the first half of the cardiac cycle is presented. The motion reconstruction results are very close to the live heart video.

  16. Tight-frame based iterative image reconstruction for spectral breast CT

    PubMed Central

    Zhao, Bo; Gao, Hao; Ding, Huanjun; Molloi, Sabee

    2013-01-01

    Purpose: To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis. Results: The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis. Conclusions: Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system. PMID:23464320

  17. Parameter space visualizer: an interactive parameter selection interface for iterative CT reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Xu, Wei; Mueller, Klaus

    2010-02-01

    Previous work indicated that using ordered subsets (OS-SIRT) for iterative CT can optimize the reconstruction performance once optimal settings for parameters such as number of subsets and relaxation factor have been identified. However, recent work also indicated that the optimal settings have dependent relations with regards to the quality of the projection data (such as SNR-level), which are hard to obtain a-priori. In addition, users may also have preferences in trading off between the dependent parameters, such as reconstruction speed and quality, which makes these (independent) parameters even more difficult to determine in an automated manner. Therefore, we devise an effective parameter space navigation interface allowing users to interactively assist parameter selection for iterative CT reconstruction algorithms (here for OS-SIRT). It is based on a 2D scatter plot with six display modes to show different features of the reconstruction results based on the user preferences. It also enables a dynamic visualization by gradual parameter alteration for illustrating the rate of impact of a given parameter constellation. Finally, we note the generality of our approach, which could be applied to assist any parameter selection related systems.

  18. Joint Reconstruction of Multi-channel, Spectral CT Data via Constrained Total Nuclear Variation Minimization

    PubMed Central

    La Rivière, Patrick J.

    2015-01-01

    We explore the use of the recently proposed “total nuclear variation” (TVN) as a regularizer for reconstructing multi-channel, spectral CT images. This convex penalty is a natural extension of the total variation (TV) to vector-valued images and has the advantage of encouraging common edge locations and a shared gradient direction among image channels. We show how it can be incorporated into a general, data-constrained reconstruction framework and derive update equations based on the first-order, primal-dual algorithm of Chambolle and Pock. Early simulation studies based on the numerical XCAT phantom indicate that the inter-channel coupling introduced by the TVN leads to better preservation of image features at high levels of regularization, compared to independent, channel-by-channel TV reconstructions. PMID:25658985

  19. Image artefact propagation in motion estimation and reconstruction in interventional cardiac C-arm CT

    NASA Astrophysics Data System (ADS)

    Müller, K.; Maier, A. K.; Schwemmer, C.; Lauritsch, G.; De Buck, S.; Wielandts, J.-Y.; Hornegger, J.; Fahrig, R.

    2014-06-01

    The acquisition of data for cardiac imaging using a C-arm computed tomography system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable three-dimensional (3D)/3D registration performed on initial 3D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3D images. In this paper, the sensitivity of the 3D/3D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing combined with the improved total variation algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical

  20. Contrast-Enhanced Ultrasound (CEUS) for Echographic Detection of Hepato Cellular Carcinoma in Cirrhotic Patients Previously Treated with Multiple Techniques: Comparison of Conventional US, Spiral CT and 3-Dimensional CEUS with Navigator Technique (3DNav CEUS)

    PubMed Central

    Giangregorio, Francesco

    2011-01-01

    A commercially available technique named “NAVIGATOR” (Esaote, Italy) easily enables a 3-D reconstruction of a single 2-D acquisition of Contrast Enhanced Ultrasound (CEUS) imaging of the whole liver (with a volumetric correction thanks to the electromagnetic device of NAVIGATOR). Aim of the study was to evaluate this “panoramic” technique in comparison with conventional US and spiral CT in the detection of new hepatic lesions. 144 cirrhotic patients (previously treated for hepato cellular carcinoma (HCC)) in follow-up with detection of 98 new nodules (N), 28 multinodular (Nmulti), 14 loco-regional regrowth (LR) 94 efficaciously treated without new nodules (neg) and four multinodular without new nodules, were submitted to 200 examinations with this new technique from November 2008 to November 2009. 3DNavCEUS was performed using SonoVue (Bracco), as contrast agent, and a machine (Technos MPX, Esaote). Spiral CT and 3DNav CEUS were performed in the same month during follow up. Sens.,Spec.,diagn.-Acc.,PPV and NPV were evaluated; comparison and differences between the techniques were obtained with chi-square (SPSS release-15). Final diagnosis was: 98 new lesions (N) (one to three), 28 multinodular HCC (Nmulti) and 14 loco-regional regrowth (LR); in 94 no more lesions were observed during follow-up; conventional US obtained: 58 N (+18 multinodularN and 8 LR), 40 false negative (+10 Nmulti and 6 LR) (sens:59.2, spec:100%, Diagn Accur:73.6, PPV:100; NPV:70.1); spiral CT obtained: 84N (+26-multinodularN and 14-LR), 14 false-negative (+2-Nmulti), and one false-positive (sens:85.7, spec:97.9%, Diagn Accur:90.9, PPV:97.7; NPV:86.8); 3DNAV obtained: 92N (+28 multinodularN and 14LR), 6 false-negative, and two false-positives (sens:93.9, spec:97.9%, Diagn Accur:95.6, PPV:97.9; NPV:93.9). 3-DNav CEUS is significantly better than US and almost similar to spiral CT for detection of new HCC. This technique, in particular, showed the presence of lesions even in the cases not

  1. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    SciTech Connect

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-07-15

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  2. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    PubMed Central

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-01-01

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  3. Automatic selection of an optimal systolic and diastolic reconstruction windows for dual-source CT coronary angiography

    NASA Astrophysics Data System (ADS)

    Seifarth, H.; Puesken, M.; Wienbeck, S.; Maintz, D.; Heindel, W.; Juergens, K.-U.

    2008-03-01

    Purpose: To assess the performance of a motion map algorithm to automatically determine the optimal systolic and diastolic reconstruction window for coronary CT Angiography using Dual Source CT. Materials and Methods: Dual Source coronary CT angiography data sets (Somatom Definition, Siemens Medical Solutions) from 50 consecutive patients were included in the analysis. Optimal systolic and diastolic reconstruction windows were determined using a motion map algorithm (BestPhase, Siemens Medical Solutions). Additionally data sets were reconstructed in 5% steps throughout the RR-interval. For each major vessel (RCA, LAD and LCX) an optimal systolic and diastolic reconstruction window was manually determined by two independent readers using volume rendering displays. Image quality was rated using a five-point scale (1 = no motion artifacts, 5 = severe motion artifacts over entire length of the vessel). Results: The mean heart rate during the scan was 72.4bpm (+/-15.8bpm). Median systolic and diastolic reconstruction windows using the BestPhase algorithm were at 37% and 73% RR. The median manually selected systolic reconstruction window was 35 %, 30% and 35% for RCA, LAD, and LCX. For all vessels the median observer selected diastolic reconstruction window was 75%. Mean image quality using the BestPhase algorithm was 2.4 +/-0.9 for systolic reconstructions and 1.9 +/-1.1 for diastolic reconstructions. Using the manual approach, the mean image quality was 1.9 +/-0.5 and 1.7 +/-0.8 respectively. There was a significant difference in image quality between automatically and manually determined systolic reconstructions (p<0.01) but there was no significant difference in image quality in diastolic reconstructions. Conclusion: Automatic determination of the optimal reconstruction interval using the BestPhase algorithm is feasible and yields reconstruction windows similar to observer selected reconstruction windows. In diastolic reconstructions overall image quality is similar

  4. Reconstruction of a cone-beam CT image via forward iterative projection matching

    SciTech Connect

    Brock, R. Scott; Docef, Alen; Murphy, Martin J.

    2010-12-15

    Purpose: To demonstrate the feasibility of reconstructing a cone-beam CT (CBCT) image by deformably altering a prior fan-beam CT (FBCT) image such that it matches the anatomy portrayed in the CBCT projection data set. Methods: A prior FBCT image of the patient is assumed to be available as a source image. A CBCT projection data set is obtained and used as a target image set. A parametrized deformation model is applied to the source FBCT image, digitally reconstructed radiographs (DRRs) that emulate the CBCT projection image geometry are calculated and compared to the target CBCT projection data, and the deformation model parameters are adjusted iteratively until the DRRs optimally match the CBCT projection data set. The resulting deformed FBCT image is hypothesized to be an accurate representation of the patient's anatomy imaged by the CBCT system. The process is demonstrated via numerical simulation. A known deformation is applied to a prior FBCT image and used to create a synthetic set of CBCT target projections. The iterative projection matching process is then applied to reconstruct the deformation represented in the synthetic target projections; the reconstructed deformation is then compared to the known deformation. The sensitivity of the process to the number of projections and the DRR/CBCT projection mismatch is explored by systematically adding noise to and perturbing the contrast of the target projections relative to the iterated source DRRs and by reducing the number of projections. Results: When there is no noise or contrast mismatch in the CBCT projection images, a set of 64 projections allows the known deformed CT image to be reconstructed to within a nRMS error of 1% and the known deformation to within a nRMS error of 7%. A CT image nRMS error of less than 4% is maintained at noise levels up to 3% of the mean projection intensity, at which the deformation error is 13%. At 1% noise level, the number of projections can be reduced to 8 while maintaining

  5. Dose reconstruction for real-time patient-specific dose estimation in CT

    SciTech Connect

    De Man, Bruno Yin, Zhye; Wu, Mingye; FitzGerald, Paul; Kalra, Mannudeep

    2015-05-15

    Purpose: Many recent computed tomography (CT) dose reduction approaches belong to one of three categories: statistical reconstruction algorithms, efficient x-ray detectors, and optimized CT acquisition schemes with precise control over the x-ray distribution. The latter category could greatly benefit from fast and accurate methods for dose estimation, which would enable real-time patient-specific protocol optimization. Methods: The authors present a new method for volumetrically reconstructing absorbed dose on a per-voxel basis, directly from the actual CT images. The authors’ specific implementation combines a distance-driven pencil-beam approach to model the first-order x-ray interactions with a set of Gaussian convolution kernels to model the higher-order x-ray interactions. The authors performed a number of 3D simulation experiments comparing the proposed method to a Monte Carlo based ground truth. Results: The authors’ results indicate that the proposed approach offers a good trade-off between accuracy and computational efficiency. The images show a good qualitative correspondence to Monte Carlo estimates. Preliminary quantitative results show errors below 10%, except in bone regions, where the authors see a bigger model mismatch. The computational complexity is similar to that of a low-resolution filtered-backprojection algorithm. Conclusions: The authors present a method for analytic dose reconstruction in CT, similar to the techniques used in radiation therapy planning with megavoltage energies. Future work will include refinements of the proposed method to improve the accuracy as well as a more extensive validation study. The proposed method is not intended to replace methods that track individual x-ray photons, but the authors expect that it may prove useful in applications where real-time patient-specific dose estimation is required.

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

    SciTech Connect

    Li, Ke; Tang, Jie; Chen, Guang-Hong

    2014-04-15

    Purpose: 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. Methods: 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{sup ®}, 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. Results: (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){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −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

  7. Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

    PubMed Central

    Eck, Brendan L.; Fahmi, Rachid; Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun; Miao, Jun; Wilson, David L.

    2015-01-01

    Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, PC. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and

  8. Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

    SciTech Connect

    Eck, Brendan L.; Fahmi, Rachid; Miao, Jun; Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun; Wilson, David L.

    2015-10-15

    Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit

  9. Assessment of volumetric noise and resolution performance for linear and nonlinear CT reconstruction methods

    SciTech Connect

    Chen, Baiyu; Christianson, Olav; Wilson, Joshua M.; Samei, Ehsan

    2014-07-15

    Purpose: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. Methods: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPS{sub task}). The in-plane resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPS{sub task} is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precision of the methodology, images of known noise and resolution properties were simulated. The NPS{sub task} and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPS{sub task} and TTF measurements with <10% error. To demonstrate the utility of this methodology, measurements were performed on a commercial CT system using five dose levels, two slice thicknesses, and three reconstruction algorithms (filtered backprojection, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 5, SAFIRE5). Results: To achieve NPS{sub task} measurements with <10% error, the

  10. SU-E-I-99: Estimation of Effective Charge Distribution by Dual-Energy CT Reconstruction

    SciTech Connect

    Sakata, D; Kida, S; Nakano, M; Masutani, Y; Nakagawa, K; Haga, A

    2014-06-01

    Purpose: Computed Tomography (CT) is a method to produce slice image of specific volume from the scanned x-ray projection images. The contrast of CT image is correlated with the attenuation coefficients of the x-ray in the object. The attenuation coefficient is strongly dependent on the x-ray energy and the effective charge of the material. The purpose of this presentation is to show the effective charge distribution predicted by CT images reconstructed with kilovoltage(kV) and megavoltage(MV) x-ray energy. Methods: The attenuation coefficients of x-ray can be characterized by cross section of photoionization and Compton scattering for the specific xray energy. In particular, the photoionization cross section is strongly correlated with the effective charge of the object. Hence we can calculate effective charge by solving the coupled equation between the attenuation coefficient and the theoretical cross section. For this study, we use the megavoltage (MV) and kilovoltage (kV) x-rays of Elekta Synergy as the dual source x-ray, and CT image of the Phantom Laboratory CatPhan is reconstructed by the filtered back projection (FBP) and iterative algorithm for cone-beam CT (CBCT). Results: We report attenuation coefficients of each component of the CatPhan specified by each x-ray source. Also the effective charge distribution is evaluated by the MV and kV dual x-ray sources. The predicted effective charges are comparable with the nominal ones. Conclusion: We developed the MV and kV dual-source CBCT reconstruction to yield the effective charge distribution. For more accuracy, it is critical to remove an effect of the scattering photon in the CBCT reconstruction algorithm. The finding will be fine reference of the effective charge of tissue and lead to the more realistic absorbed-dose calculation. This work was partly supported by the JSPS Core-to-Core Program(No. 23003), and this work was partly supported by JSPS KAKENHI 24234567.

  11. A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging

    SciTech Connect

    Yan, Hao; Folkerts, Michael; Jiang, Steve B. E-mail: steve.jiang@UTSouthwestern.edu; Jia, Xun E-mail: steve.jiang@UTSouthwestern.edu; Zhen, Xin; Li, Yongbao; Pan, Tinsu; Cervino, Laura

    2014-07-15

    Purpose: 4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. Methods: The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. Results: The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3–0.5 mm for patients 1–3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1–1.5 min per phase

  12. Three-dimensional focus of attention for iterative cone-beam micro-CT reconstruction

    NASA Astrophysics Data System (ADS)

    Benson, T. M.; Gregor, J.

    2006-09-01

    Three-dimensional iterative reconstruction of high-resolution, circular orbit cone-beam x-ray CT data is often considered impractical due to the demand for vast amounts of computer cycles and associated memory. In this paper, we show that the computational burden can be reduced by limiting the reconstruction to a small, well-defined portion of the image volume. We first discuss using the support region defined by the set of voxels covered by all of the projection views. We then present a data-driven preprocessing technique called focus of attention that heuristically separates both image and projection data into object and background before reconstruction, thereby further reducing the reconstruction region of interest. We present experimental results for both methods based on mouse data and a parallelized implementation of the SIRT algorithm. The computational savings associated with the support region are substantial. However, the results for focus of attention are even more impressive in that only about one quarter of the computer cycles and memory are needed compared with reconstruction of the entire image volume. The image quality is not compromised by either method.

  13. Line Integral Alternating Minimization Algorithm for Dual-Energy X-Ray CT Image Reconstruction.

    PubMed

    Chen, Yaqi; O'Sullivan, Joseph A; Politte, David G; Evans, Joshua D; Han, Dong; Whiting, Bruce R; Williamson, Jeffrey F

    2016-02-01

    We propose a new algorithm, called line integral alternating minimization (LIAM), for dual-energy X-ray CT image reconstruction. Instead of obtaining component images by minimizing the discrepancy between the data and the mean estimates, LIAM allows for a tunable discrepancy between the basis material projections and the basis sinograms. A parameter is introduced that controls the size of this discrepancy, and with this parameter the new algorithm can continuously go from a two-step approach to the joint estimation approach. LIAM alternates between iteratively updating the line integrals of the component images and reconstruction of the component images using an image iterative deblurring algorithm. An edge-preserving penalty function can be incorporated in the iterative deblurring step to decrease the roughness in component images. Images from both simulated and experimentally acquired sinograms from a clinical scanner were reconstructed by LIAM while varying the regularization parameters to identify good choices. The results from the dual-energy alternating minimization algorithm applied to the same data were used for comparison. Using a small fraction of the computation time of dual-energy alternating minimization, LIAM achieves better accuracy of the component images in the presence of Poisson noise for simulated data reconstruction and achieves the same level of accuracy for real data reconstruction.

  14. Iterative reconstruction of cone-beam CT data on a cluster

    NASA Astrophysics Data System (ADS)

    Benson, Thomas M.; Gregor, Jens

    2007-02-01

    Three-dimensional iterative reconstruction of large CT data sets poses several challenges in terms of the associated computational and memory requirements. In this paper, we present results obtained by implementing a computational framework for reconstructing axial cone-beam CT data using a cluster of inexpensive dualprocessor PCs. In particular, we discuss our parallelization approach, which uses POSIX threads and message passing (MPI) for local and remote load distribution, as well as the interaction of that load distribution with the implementation of ordered subset based algorithms. We also consider a heuristic data-driven 3D focus of attention algorithm that reduces the amount of data that must be considered for many data sets. Furthermore, we present a modification to the SIRT algorithm that reduces the amount of data that must be communicated between processes. Finally, we introduce a method of separating the work in such a way that some computation can be overlapped with the MPI communication thus further reducing the overall run-time. We summarize the performance results using reconstructions of experimental data.

  15. Low-dose multiphase abdominal CT reconstruction with phase-induced swap prior

    NASA Astrophysics Data System (ADS)

    Selim, Mona; Rashed, Essam A.; Kudo, Hiroyuki

    2016-10-01

    Multiphase abdominal CT is an imaging protocol in which the patient is scanned at different phases before and after the injection of a contrast agent. Reconstructed images with different concentrations of contrast material provide useful information for effective detection of abnormalities. However, several scanning during a short period of time eventually increase the patient radiation dose to a remarkable value up to a risky level. Reducing the patient dose by modulating the x-ray tube current or acquiring the projection data through a small number of views are known to degrade the image quality and reduce the possibility to be useful for diagnosis purpose. In this work, we propose a novel multiphase abdominal CT imaging protocol with patient dose reduction and high image quality. The image reconstruction cost function consists of two terms, namely the data fidelity term and penalty term to enforce the anatomical similarity in successive contrast phase reconstruction. The prior information, named phase-induced swap prior (PISP) is computed using total variation minimization of image acquired from different contrast phases. The new method is evaluated through a simulation study using digital abdominal phantom and real data and results are promising.

  16. Acceleration of EM-Based 3D CT Reconstruction Using FPGA.

    PubMed

    Choi, Young-Kyu; Cong, Jason

    2016-06-01

    Reducing radiation doses is one of the key concerns in computed tomography (CT) based 3D reconstruction. Although iterative methods such as the expectation maximization (EM) algorithm can be used to address this issue, applying this algorithm to practice is difficult due to the long execution time. Our goal is to decrease this long execution time to an order of a few minutes, so that low-dose 3D reconstruction can be performed even in time-critical events. In this paper we introduce a novel parallel scheme that takes advantage of numerous block RAMs on field-programmable gate arrays (FPGAs). Also, an external memory bandwidth reduction strategy is presented to reuse both the sinogram and the voxel intensity. Moreover, a customized processing engine based on the FPGA is presented to increase overall throughput while reducing the logic consumption. Finally, a hardware and software flow is proposed to quickly construct a design for various CT machines. The complete reconstruction system is implemented on an FPGA-based server-class node. Experiments on actual patient data show that a 26.9 × speedup can be achieved over a 16-thread multicore CPU implementation.

  17. A fast CT reconstruction scheme for a general multi-core PC.

    PubMed

    Zeng, Kai; Bai, Erwei; Wang, Ge

    2007-01-01

    Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors.

  18. Reconstruction of difference in sequential CT studies using penalized likelihood estimation

    PubMed Central

    Pourmorteza, A; Dang, H; Siewerdsen, J H; Stayman, J W

    2016-01-01

    Characterization of anatomical change and other differences is important in sequential computed tomography (CT) imaging, where a high-fidelity patient-specific prior image is typically present, but is not used, in the reconstruction of subsequent anatomical states. Here, we introduce a penalized likelihood (PL) method called reconstruction of difference (RoD) to directly reconstruct a difference image volume using both the current projection data and the (unregistered) prior image integrated into the forward model for the measurement data. The algorithm utilizes an alternating minimization to find both the registration and reconstruction estimates. This formulation allows direct control over the image properties of the difference image, permitting regularization strategies that inhibit noise and structural differences due to inconsistencies between the prior image and the current data.Additionally, if the change is known to be local, RoD allows local acquisition and reconstruction, as opposed to traditional model-based approaches that require a full support field of view (or other modifications). We compared the performance of RoD to a standard PL algorithm, in simulation studies and using test-bench cone-beam CT data. The performances of local and global RoD approaches were similar, with local RoD providing a significant computational speedup. In comparison across a range of data with differing fidelity, the local RoD approach consistently showed lower error (with respect to a truth image) than PL in both noisy data and sparsely sampled projection scenarios. In a study of the prior image registration performance of RoD, a clinically reasonable capture ranges were demonstrated. Lastly, the registration algorithm had a broad capture range and the error for reconstruction of CT data was 35% and 20% less than filtered back-projection for RoD and PL, respectively. The RoD has potential for delivering high-quality difference images in a range of sequential clinical

  19. Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

    SciTech Connect

    Solomon, Justin; Samei, Ehsan

    2014-09-15

    Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

  20. Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

    SciTech Connect

    Brady, S. L.; Yee, B. S.; Kaufman, R. A.

    2012-09-15

    Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR Trade-Mark-Sign ) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR Trade-Mark-Sign . Empirically derived dose reduction limits were established for ASiR Trade-Mark-Sign for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%-100% ASiR Trade-Mark-Sign blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR Trade-Mark-Sign implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR Trade-Mark-Sign reconstruction to maintain noise equivalence of the 0% ASiR Trade-Mark-Sign image. Results: The ASiR Trade-Mark-Sign algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR Trade-Mark-Sign reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR Trade-Mark-Sign presented a more

  1. A curve-filtered FDK (C-FDK) reconstruction algorithm for circular cone-beam CT.

    PubMed

    Li, Liang; Xing, Yuxiang; Chen, Zhiqiang; Zhang, Li; Kang, Kejun

    2011-01-01

    Circular cone-beam CT is one of the most popular configurations in both medical and industrial applications. The FDK algorithm is the most popular method for circular cone-beam CT. However, with increasing cone-angle the cone-beam artifacts associated with the FDK algorithm deteriorate because the circular trajectory does not satisfy the data sufficiency condition. Along with an experimental evaluation and verification, this paper proposed a curve-filtered FDK (C-FDK) algorithm. First, cone-parallel projections are rebinned from the native cone-beam geometry in two separate directions. C-FDK rebins and filters projections along different curves from T-FDK in the centrally virtual detector plane. Then, numerical experiments are done to validate the effectiveness of the proposed algorithm by comparing with both FDK and T-FDK reconstruction. Without any other extra trajectories supplemental to the circular orbit, C-FDK has a visible image quality improvement.

  2. Reconstruction of 4D-CT data sets acquired during free breathing for the analysis of respiratory motion

    NASA Astrophysics Data System (ADS)

    Ehrhardt, Jan; Werner, Rene; Frenzel, Thorsten; Säring, Dennis; Lu, Wei; Low, Daniel; Handels, Heinz

    2006-03-01

    Respiratory motion is a significant source of error in radiotherapy treatment planning. 4D-CT data sets can be useful to measure the impact of organ motion caused by breathing. But modern CT scanners can only scan a limited region of the body simultaneously and patients have to be scanned in segments consisting of multiple slices. For studying free breathing motion multislice CT scans can be collected simultaneously with digital spirometry over several breathing cycles. The 4D data set is assembled by sorting the free breathing multislice CT scans according to the couch position and the tidal volume. But artifacts can occur because there are no data segments for exactly the same tidal volume and all couch positions. We present an optical flow based method for the reconstruction of 4D-CT data sets from multislice CT scans, which are collected simultaneously with digital spirometry. The optical flow between the scans is estimated by a non-linear registration method. The calculated velocity field is used to reconstruct a 4D-CT data set by interpolating data at user-defined tidal volumes. By this technique, artifacts can be reduced significantly. The reconstructed 4D-CT data sets are used for studying inner organ motion during the respiratory cycle. The procedures described were applied to reconstruct 4D-CT data sets for four tumour patients who have been scanned during free breathing. The reconstructed 4D data sets were used to quantify organ displacements and to visualize the abdominothoracic organ motion.

  3. Effect of voxel size on the accuracy of 3D reconstructions with cone beam CT

    PubMed Central

    Maret, D; Telmon, N; Peters, O A; Lepage, B; Treil, J; Inglèse, J M; Peyre, A; Kahn, J L; Sixou, M

    2012-01-01

    Objectives The various types of cone beam CT (CBCT) differ in several technical characteristics, notably their spatial resolution, which is defined by the acquisition voxel size. However, data are still lacking on the effects of voxel size on the metric accuracy of three-dimensional (3D) reconstructions. This study was designed to assess the effect of isotropic voxel size on the 3D reconstruction accuracy and reproducibility of CBCT data. Methods The study sample comprised 70 teeth (from the Institut d’Anatomie Normale, Strasbourg, France). The teeth were scanned with a KODAK 9500 3D® CBCT (Carestream Health, Inc., Marne-la-Vallée, France), which has two voxel sizes: 200 µm (CBCT 200 µm group) and 300 µm (CBCT 300 µm group). These teeth had also been scanned with the KODAK 9000 3D® CBCT (Carestream Health, Inc.) (CBCT 76 µm group) and the SCANCO Medical micro-CT XtremeCT (SCANCO Medical, Brüttisellen, Switzerland) (micro-CT 41 µm group) considered as references. After semi-automatic segmentation with AMIRA® software (Visualization Sciences Group, Burlington, MA), tooth volumetric measurements were obtained. Results The Bland–Altman method showed no difference in tooth volumes despite a slight underestimation for the CBCT 200 µm and 300 µm groups compared with the two reference groups. The underestimation was statistically significant for the volumetric measurements of the CBCT 300 µm group relative to the two reference groups (Passing–Bablok method). Conclusions CBCT is not only a tool that helps in diagnosis and detection but it has the complementary advantage of being a measuring instrument, the accuracy of which appears connected to the size of the voxels. Future applications of such measurements with CBCT are discussed. PMID:23166362

  4. Dose reduction in CT urography and vasculature phantom studies using model-based iterative reconstruction.

    PubMed

    Page, Leland; Wei, Wei; Kundra, Vikas; Rong, John

    2016-11-08

    To evaluate the feasibility of radiation dose reduction using model-based iterative reconstruction (MBIR) for evaluating the ureters and vasculature in a phantom, a tissue-equivalent CT dose phantom was scanned using a 64-channel CT scan-ner. Tubes of varying diameters filled with different dilutions of a contrast agent, simulating ureters or vessels, were inserted into the center of the phantom. Each combination was scanned using an existing renal protocol at 140 kVp or 120 kVp, yielding a display volumetric CT dose index (CTDIvol) of 24 mGy. The scans were repeated using reduced scan techniques to achieve lower radiation doses down to 0.8 mGy. The images were reconstructed using filtered back-projection (FBP) and model-based iterative reconstruction (MBIR). The noise and contrast-to-noise ratio (CNR) was measured for each contrast object. Comparisons between the two reconstruction methods at different dose levels were evaluated using a factorial design. At each CTDIvol the measured image noise was lower using MBIR compared to FBP (p < 0.0001). At low doses, the percent change in measured image noise between FBP and MBIR was larger. For the 12 mm object simulating a ureter or large vessel with an HU of 600, the measured CNR using MBIR at a CTDIvol of 1.7 mGy was greater than the CNR of FBP at a CTIDvol of 24 mGy (p < 0.0001). For the 5 mm object simulating a medium-sized vessel with a HU of 250, the mea-sured CNR using MBIR at a CTDIvol of 1.7 mGy was equivalent to that of FBP at a CTDIvol of 24 mGy. For the 2 mm, 100 HU object simulating a small vessel, the measured CNR using MBIR at a CTDIvol of 1.7 mGy was equivalent to that of FBP at a CTDIvol of 24 mGy. Low-dose (3.6 mGy) CT imaging of vasculature and ureter phantoms using MBIR results in similar noise and CNR compared to FBP at approximately one-sixth the dose. This suggests that, using MBIR, a one milliSievert exam of the ureters and vasculature may be clinically possible whilst still maintaining adequate

  5. Multiplanar CT reconstruction of the jaw: a new way for implant diagnostics

    NASA Astrophysics Data System (ADS)

    Gursky, S.; Wittek, Werner; Wilke, Walter; Schulz, H.; Lieberenz, S.

    1990-11-01

    For preoperative planning of dental implantations pictorial representations are required that permit to evaluate the size of teeth holes, size and structure of jaw bones, position of the mandibular channel and of the alveolar nerve. Since normal transaxial. CT images do not meet these requirements special secondary reconstructions adapted to jaw anatomy are necessary: -panoramic secondary cuts The cut line follows jaw curvature and represents a similar view as orthopantomographic pictures. (see Fig.1) -oblique secondary cuts That are plane cuts perpendicular to the panoramic cut line. (see Fig.2)

  6. Agenesis of dorsal pancreas confirmed by three-dimensional reconstruction CT

    PubMed Central

    Zhou, Yang; Chen, Munan; Liu, Yang

    2014-01-01

    Agenesis of the dorsal pancreas (ADP) is a rare congenital pancreatic malformation in which all or part of the dorsal pancreatic body is absent. ADP is usually confirmed by magnetic resonance cholangiopancreatography (MRCP) or endoscopic retrograde cholangiopancreatography (ERCP), but these methods are undesirable to patients because of strict limitations or invasiveness. We propose abdominal contrast-enhanced and three-dimensional reconstruction CT images as an improved method for ADP diagnosis, and present a case study of ADP confirmed with these methods. PMID:25356189

  7. Image reconstruction and image quality evaluation for a 16-slice CT scanner.

    PubMed

    Flohr, Th; Stierstorfer, K; Bruder, H; Simon, J; Polacin, A; Schaller, S

    2003-05-01

    We present a theoretical overview and a performance evaluation of a novel approximate reconstruction algorithm for cone-beam spiral CT, the adaptive multiple plane reconstruction (AMPR), which has been introduced by Schaller, Flohr et al. [Proc. SPIE Int. Symp. Med. Imag. 4322, 113-127 (2001)] AMPR has been implemented in a recently introduced 16-slice CT scanner. We present a detailed algorithmic description of AMPR which allows for a free selection of the spiral pitch. We show that dose utilization is better than 90% independent of the pitch. We give an overview on the z-reformation functions chosen to allow for a variable selection of the spiral slice width at arbitrary pitch values. To investigate AMPR image quality we present images of anthropomorphic phantoms and initial patient results. We present measurements of spiral slice sensitivity profiles (SSPs) and measurements of the maximum achievable transverse resolution, both in the isocenter and off-center. We discuss the pitch dependence of image noise measured in a centered 20 cm water phantom. Using the AMPR approach, cone-beam artifacts are considerably reduced for the 16-slice scanner investigated. Image quality in MPRs is independent of the pitch and equivalent to a single-slice CT system at pitch p approximately 1.5. The full width at half-maximum (FWHM) of the spiral SSPs shows only minor variations as a function of the pitch, nominal, and measured values differ by less than 0.2 mm. With 16 x 0.75 mm collimation, the measured FWHM of the smallest reconstructed slice is about 0.9 mm. Using this slice width and overlapping image reconstruction, cylindrical holes with 0.6 mm diameter can be resolved in a z-resolution phantom. Image noise for constant effective mAs is nearly independent of the pitch. Measured and theoretically expected dose utilization are in good agreement. Meanwhile, clinical practice has demonstrated the excellent image quality and the increased diagnostic capability that is obtained

  8. Statistical modeling challenges in model-based reconstruction for x-ray CT

    NASA Astrophysics Data System (ADS)

    Zhang, Ruoqiao; Chang, Aaron; Thibault, Jean-Baptiste; Sauer, Ken; Bouman, Charles

    2013-02-01

    Model- based iterative reconstruction (MBIR) is increasingly widely applied as an improvement over conventional, deterministic methods of image reconstruction in X-ray CT. A primary advantage of MBIR is potentially dras­ tically reduced dosage without diagnostic quality loss. Early success of the method has naturally led to growing numbers of scans at very low dose, presenting data which does not match well the simple statistical models heretofore considered adequate. This paper addresses several issues arising in limiting cases which call for refine­ ment of standard data models. The emergence of electronic noise as a significant contributor to uncertainty, and bias of sinogram values in photon-starved measurements are demonstrated to be important modeling problems in this new environment. We present also possible ameliorations to several of these low-dosage estimation issues.

  9. The influence of CT dose and reconstruction parameters on automated detection of small pulmonary nodules

    NASA Astrophysics Data System (ADS)

    Ochs, Robert; Angel, Erin; Boedeker, Kirsten; Petkovska, Iva; Panknin, Christoph; Goldin, Jonathan; Aberle, Denise; McNitt-Gray, Michael; Brown, Matthew

    2006-03-01

    The aim of our investigation was to assess the influence of both CT acquisition dose and reconstruction kernel on computer-aided detection (CAD) of pulmonary nodules. Our hypothesis is that the detection of small nodules is affected by the noise characteristics of the image and the signal to noise ratio of the nodule and bronchiovascular anatomy. Knowledge gained from this experiment will assist in developing an advanced CAD system designed to detect smaller and more subtle nodules with minimal false positives. Eleven research subjects were selected from the Lung Image Database Consortium (LIDC) database based on our inclusion criteria of: 1) having at least one nodule and 2) available raw CT projection data for the series that our institution submitted to the LIDC study. Using the original raw projection data, research software simulated raw projection data acquired with a dose reduced 32-40% from the original scan. Projection data for both dose levels was reconstructed with smooth to very sharp kernels (B10f, B30f, B50f, and B70f). The resulting series were used to investigate the influence of dose and reconstruction kernel on CAD performance. A prototype CAD system was used to investigate changes in sensitivity and false positives with varying imaging parameters. In a sub-study, the prototype system was compared to a commercial CAD system. We did not have enough subjects to conclude significance, but the results indicate our research system had a higher sensitivity with the smooth or medium reconstruction kernels than with the sharper kernels. The sensitivity was similar for both dose levels. The false positive rate was higher with the smooth kernels and the lower dose levels.

  10. Total variation superiorization in dual-energy CT reconstruction for proton therapy treatment planning

    NASA Astrophysics Data System (ADS)

    Zhu, Jiahua; Penfold, Scott

    2017-04-01

    Proton therapy is a precise form of radiotherapy in which the range of an energetic beam of protons within a patient must be accurately known. The current approach based on single-energy computed tomography (SECT) can lead to uncertainties in the proton range of approximately 3%. This range of uncertainty may lead to under-dosing of the tumour or over-dosing of healthy tissues. Dual-energy CT (DECT) theoretically has the potential to reduce these range uncertainties by quantifying electron density and the effective atomic number. In practice, however, DECT images reconstructed with filtered backprojection (FBP) tend to suffer from high levels of noise. The objective of the current work was to examine the effect of total variation superiorization (TVS) on proton therapy planning accuracy when compared with FBP. A virtual CT scanner was created with the Monte Carlo toolkit Geant4. Tomographic images were reconstructed with FBP and TVS combined with diagonally relaxed orthogonal projections (TVS-DROP). A total variation minimization (TVM) filter was also applied to the image reconstructed with FBP (FBP-TVM). Quantitative accuracy and variance of proton relative stopping power (RSP) derived from each image set was assessed. Mean RSPs were comparable with each image; however, the standard deviation of pixel values with TVS-DROP was reduced by a factor of 0.44 compared with the FBP image and a factor of 0.66 when compared with the FBP-TVM image. Proton doses calculated with the TVS-DROP image set were also better able to predict a reference dose distribution when compared with the FBP and FBP-TVM image sets. The study demonstrated the potential advantages of TVS-DROP as an image reconstruction method for DECT applied to proton therapy treatment planning.

  11. Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

    SciTech Connect

    Gang, Grace J.; Stayman, J. Webster; Zbijewski, Wojciech; Siewerdsen, Jeffrey H.

    2014-08-15

    Purpose: Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction. Methods: Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according toFessler [“Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography,” IEEE Trans. Image Process. 5(3), 493–506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map. Results: Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP

  12. Directional sinogram interpolation for motion weighted 4D cone-beam CT reconstruction

    NASA Astrophysics Data System (ADS)

    Zhang, Hua; Kruis, Matthijs; Sonke, Jan-Jakob

    2017-03-01

    The image quality of respiratory sorted four-dimensional (4D) cone-beam (CB) computed tomography (CT) is often limited by streak artifacts due to insufficient projections. A motion weighted reconstruction (MWR) method is proposed to decrease streak artifacts and improve image quality. Firstly, respiratory correlated CBCT projections were interpolated by directional sinogram interpolation (DSI) to generate additional CB projections for each phase and subsequently reconstructed. Secondly, local motion was estimated by deformable image registration of the interpolated 4D CBCT. Thirdly, a regular 3D FDK CBCT was reconstructed from the non-interpolated projections. Finally, weights were assigned to each voxel, based on the local motion, and then were used to combine the 3D FDK CBCT and interpolated 4D CBCT to generate the final 4D image. MWR method was compared with regular 4D CBCT scans as well as McKinnon and Bates (MKB) based reconstructions. Comparisons were made in terms of (1) comparing the steepness of an extracted profile from the boundary of the region-of-interest (ROI), (2) contrast-to-noise ratio (CNR) inside certain ROIs, and (3) the root-mean-square-error (RMSE) between the planning CT and CBCT inside a homogeneous moving region. Comparisons were made for both a phantom and four patient scans. In a 4D phantom, RMSE were reduced by 24.7% and 38.7% for MKB and MWR respectively, compared to conventional 4D CBCT. Meanwhile, interpolation induced blur was minimal in static regions for MWR based reconstructions. In regions with considerable respiratory motion, image blur using MWR is less than the MKB and 3D Feldkamp (FDK) methods. In the lung cancer patients, average CNRs of MKB, DSI and MWR improved by a factor 1.7, 2.8 and 3.5 respectively relative to 4D FDK. MWR effectively reduces RMSE in 4D cone-beam CT and improves the image quality in both the static and respiratory moving regions compared to 4D FDK and MKB methods.

  13. Feasibility of GPU-assisted iterative image reconstruction for mobile C-arm CT

    NASA Astrophysics Data System (ADS)

    Pan, Yongsheng; Whitaker, Ross; Cheryauka, Arvi; Ferguson, Dave

    2009-02-01

    Computed tomography (CT) has been extensively studied and widely used for a variety of medical applications. The reconstruction of 3D images from a projection series is an important aspect of the modality. Reconstruction by filtered backprojection (FBP) is used by most manufacturers because of speed, ease of implementation, and relatively few parameters. Iterative reconstruction methods have a significant potential to provide superior performance with incomplete or noisy data, or with less than ideal geometries, such as cone-beam systems. However, iterative methods have a high computational cost, and regularization is usually required to reduce the effects of noise. The simultaneous algebraic reconstruction technique (SART) is studied in this paper, where the Feldkamp method (FDK) for filtered back projection is used as an initialization for iterative SART. Additionally, graphics hardware is utilized to increase the speed of SART implementation. Nvidia processors and compute unified device architecture (CUDA) form the platform for GPU computation. Total variation (TV) minimization is applied for the regularization of SART results. Preliminary results of SART on 3-D Shepp-Logan phantom using using TV regularization and GPU computation are presented in this paper. Potential improvements of the proposed framework are also discussed.

  14. Iterative CT reconstruction with small pixel size: distance-driven forward projector versus Joseph's

    NASA Astrophysics Data System (ADS)

    Hahn, K.; Rassner, U.; Davidson, H. C.; Schöndube, H.; Stierstorfer, K.; Hornegger, J.; Noo, F.

    2015-03-01

    Over the last few years, iterative reconstruction methods have become an important research topic in x-ray CT imaging. This effort is motivated by increasing evidence that such methods may enable significant savings in terms of dose imparted to the patient. Conceptually, iterative reconstruction methods involve two important ingredients: the statistical model, which includes the forward projector, and a priori information in the image domain, which is expressed using a regularizer. Most often, the image pixel size is chosen to be equal (or close) to the detector pixel size (at field-of-view center). However, there are applications for which a smaller pixel size is desired. In this investigation, we focus on reconstruction with a pixel size that is twice smaller than the detector pixel size. Using such a small pixel size implies a large increase in computational effort when using the distance-driven method for forward projection, which models the detector size. On the other hand, the more efficient method of Joseph will create imbalances in the reconstruction of each pixel, in the sense that there will be large differences in the way each projection contributes to the pixels. The purpose of this work is to evaluate the impact of these imbalances on image quality in comparison with utilization of the distance-driven method. The evaluation involves computational effort, bias and noise metrics, and LROC analysis using human observers. The results show that Joseph's method largely remains attractive.

  15. Iterative reconstruction optimisations for high angle cone-beam micro-CT

    NASA Astrophysics Data System (ADS)

    Recur, B.; Fauconneau, M.; Kingston, A.; Myers, G.; Sheppard, A.

    2014-09-01

    We address several acquisition questions that have arisen for the high cone-angle helical-scanning micro-CT facility developed at the Australian National University. These challenges are generally known in medical and industrial cone-beam scanners but can be neglected in these systems. For our large datasets, with more than 20483 voxels, minimising the number of operations (or iterations) is crucial. Large cone-angles enable high signal-to-noise ratio imaging and a large helical pitch to be used. This introduces two challenges: (i) non-uniform resolution throughout the reconstruction, (ii) over-scan beyond the region-of-interest significantly increases re- quired reconstructed volume size. Challenge (i) can be addressed by using a double-helix or lower pitch helix but both solutions slow down iterations. Challenge (ii) can also be improved by using a lower pitch helix but results in more projections slowing down iterations. This may be overcome using less projections per revolution but leads to more iterations required. Here we assume a given total time for acquisition and a given reconstruction technique (SART) and seek to identify the optimal trajectory and number of projections per revolution in order to produce the best tomogram, minimise reconstruction time required, and minimise memory requirements.

  16. Regularization Designs for Uniform Spatial Resolution and Noise Properties in Statistical Image Reconstruction for 3D X-ray CT

    PubMed Central

    Cho, Jang Hwan; Fessler, Jeffrey A.

    2014-01-01

    Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT. This paper extends the regularization method proposed in [1] to 3D cone-beam CT by introducing a hypothetical scanning geometry that helps address the sampling properties. The proposed regularization designs were compared with the original method in [1] with both phantom simulation and clinical reconstruction in 3D axial X-ray CT. The proposed regularization methods yield improved spatial resolution or noise uniformity in statistical image reconstruction for short-scan axial cone-beam CT. PMID:25361500

  17. Regularization designs for uniform spatial resolution and noise properties in statistical image reconstruction for 3-D X-ray CT.

    PubMed

    Cho, Jang Hwan; Fessler, Jeffrey A

    2015-02-01

    Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT. This paper extends the regularization method proposed in to 3-D cone-beam CT by introducing a hypothetical scanning geometry that helps address the sampling properties. The proposed regularization designs were compared with the original method in with both phantom simulation and clinical reconstruction in 3-D axial X-ray CT. The proposed regularization methods yield improved spatial resolution or noise uniformity in statistical image reconstruction for short-scan axial cone-beam CT.

  18. SU-E-I-33: Initial Evaluation of Model-Based Iterative CT Reconstruction Using Standard Image Quality Phantoms

    SciTech Connect

    Gingold, E; Dave, J

    2014-06-01

    Purpose: The purpose of this study was to compare a new model-based iterative reconstruction with existing reconstruction methods (filtered backprojection and basic iterative reconstruction) using quantitative analysis of standard image quality phantom images. Methods: An ACR accreditation phantom (Gammex 464) and a CATPHAN600 phantom were scanned using 3 routine clinical acquisition protocols (adult axial brain, adult abdomen, and pediatric abdomen) on a Philips iCT system. Each scan was acquired using default conditions and 75%, 50% and 25% dose levels. Images were reconstructed using standard filtered backprojection (FBP), conventional iterative reconstruction (iDose4) and a prototype model-based iterative reconstruction (IMR). Phantom measurements included CT number accuracy, contrast to noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD), and noise power spectrum (NPS). Results: The choice of reconstruction method had no effect on CT number accuracy, or MTF (p<0.01). The CNR of a 6 HU contrast target was improved by 1–67% with iDose4 relative to FBP, while IMR improved CNR by 145–367% across all protocols and dose levels. Within each scan protocol, the CNR improvement from IMR vs FBP showed a general trend of greater improvement at lower dose levels. NPS magnitude was greatest for FBP and lowest for IMR. The NPS of the IMR reconstruction showed a pronounced decrease with increasing spatial frequency, consistent with the unusual noise texture seen in IMR images. Conclusion: Iterative Model Reconstruction reduces noise and improves contrast-to-noise ratio without sacrificing spatial resolution in CT phantom images. This offers the possibility of radiation dose reduction and improved low contrast detectability compared with filtered backprojection or conventional iterative reconstruction.

  19. Non-local total-variation (NLTV) minimization combined with reweighted L1-norm for compressed sensing CT reconstruction

    NASA Astrophysics Data System (ADS)

    Kim, Hojin; Chen, Josephine; Wang, Adam; Chuang, Cynthia; Held, Mareike; Pouliot, Jean

    2016-09-01

    The compressed sensing (CS) technique has been employed to reconstruct CT/CBCT images from fewer projections as it is designed to recover a sparse signal from highly under-sampled measurements. Since the CT image itself cannot be sparse, a variety of transforms were developed to make the image sufficiently sparse. The total-variation (TV) transform with local image gradient in L1-norm was adopted in most cases. This approach, however, which utilizes very local information and penalizes the weight at a constant rate regardless of different degrees of spatial gradient, may not produce qualified reconstructed images from noise-contaminated CT projection data. This work presents a new non-local operator of total-variation (NLTV) to overcome the deficits stated above by utilizing a more global search and non-uniform weight penalization in reconstruction. To further improve the reconstructed results, a reweighted L1-norm that approximates the ideal sparse signal recovery of the L0-norm is incorporated into the NLTV reconstruction with additional iterates. This study tested the proposed reconstruction method (reweighted NLTV) from under-sampled projections of 4 objects and 5 experiments (1 digital phantom with low and high noise scenarios, 1 pelvic CT, and 2 CBCT images). We assessed its performance against the conventional TV, NLTV and reweighted TV transforms in the tissue contrast, reconstruction accuracy, and imaging resolution by comparing contrast-noise-ratio (CNR), normalized root-mean square error (nRMSE), and profiles of the reconstructed images. Relative to the conventional NLTV, combining the reweighted L1-norm with NLTV further enhanced the CNRs by 2-4 times and improved reconstruction accuracy. Overall, except for the digital phantom with low noise simulation, our proposed algorithm produced the reconstructed image with the lowest nRMSEs and the highest CNRs for each experiment.

  20. Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

    NASA Astrophysics Data System (ADS)

    Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

    2011-03-01

    Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

  1. CT reconstruction from few-views with anisotropic edge-guided total variance

    NASA Astrophysics Data System (ADS)

    Rong, Junyan; Liu, Wenlei; Gao, Peng; Liao, Qimei; Jiao, Chun; Ma, Jianhua; Lu, Hongbing

    2016-06-01

    To overcome the oversmoothing drawback in the edge areas when reconstructing few-view CT with total variation (TV) minimization, in this paper, we propose an anisotropic edge-guided TV minimization framework for few-view CT reconstruction. In the framework, anisotropic TV is summed with pre-weighted image gradient and then used as the object function for minimizing. It includes edge-guided TV minimization (EGTV) and edge-guided adaptive-weighted TV minimization (EGAwTV) algorithms. For EGTV algorithm, the weights of the TV discretization term are updated by anisotropic edge information detected from the image, whereas the weights for EGAwTV are determined based on edge information and local image-intensity gradients. To solve the minimization problem of the proposed algorithm, a similar TV-based minimization implementation is developed to address the raw data fidelity and other constraints. The evaluation results using both computer simulations with the Shepp-Logan phantom and experimental data from a physical phantom demonstrate that the proposed algorithms exhibit noticeable gains in the merits of spatial resolution compared with the conventional TV and other modified TV algorithms.

  2. Sparse signal reconstruction from polychromatic X-ray CT measurements via mass attenuation discretization

    SciTech Connect

    Gu, Renliang; Dogandžić, Aleksandar

    2014-02-18

    We propose a method for reconstructing sparse images from polychromatic x-ray computed tomography (ct) measurements via mass attenuation coefficient discretization. The material of the inspected object and the incident spectrum are assumed to be unknown. We rewrite the Lambert-Beer’s law in terms of integral expressions of mass attenuation and discretize the resulting integrals. We then present a penalized constrained least-squares optimization approach for reconstructing the underlying object from log-domain measurements, where an active set approach is employed to estimate incident energy density parameters and the nonnegativity and sparsity of the image density map are imposed using negative-energy and smooth ℓ{sub 1}-norm penalty terms. We propose a two-step scheme for refining the mass attenuation discretization grid by using higher sampling rate over the range with higher photon energy, and eliminating the discretization points that have little effect on accuracy of the forward projection model. This refinement allows us to successfully handle the characteristic lines (Dirac impulses) in the incident energy density spectrum. We compare the proposed method with the standard filtered backprojection, which ignores the polychromatic nature of the measurements and sparsity of the image density map. Numerical simulations using both realistic simulated and real x-ray ct data are presented.

  3. Multi-material decomposition using statistical image reconstruction for spectral CT.

    PubMed

    Long, Yong; Fessler, Jeffrey A

    2014-08-01

    Spectral computed tomography (CT) provides information on material characterization and quantification because of its ability to separate different basis materials. Dual-energy (DE) CT provides two sets of measurements at two different source energies. In principle, two materials can be accurately decomposed from DECT measurements. However, many clinical and industrial applications require three or more material images. For triple-material decomposition, a third constraint, such as volume conservation, mass conservation or both, is required to solve three sets of unknowns from two sets of measurements. The recently proposed flexible image-domain (ID) multi-material decomposition) method assumes each pixel contains at most three materials out of several possible materials and decomposes a mixture pixel by pixel. We propose a penalized-likelihood (PL) method with edge-preserving regularizers for each material to reconstruct multi-material images using a similar constraint from sinogram data. We develop an optimization transfer method with a series of pixel-wise separable quadratic surrogate (PWSQS) functions to monotonically decrease the complicated PL cost function. The PWSQS algorithm separates pixels to allow simultaneous update of all pixels, but keeps the basis materials coupled to allow faster convergence rate than our previous proposed material- and pixel-wise SQS algorithms. Comparing with the ID method using 2-D fan-beam simulations, the PL method greatly reduced noise, streak and cross-talk artifacts in the reconstructed basis component images, and achieved much smaller root mean square errors.

  4. Fast X-Ray CT Image Reconstruction Using a Linearized Augmented Lagrangian Method with Ordered Subsets

    PubMed Central

    Nien, Hung; Fessler, Jeffrey A.

    2014-01-01

    Augmented Lagrangian (AL) methods for solving convex optimization problems with linear constraints are attractive for imaging applications with composite cost functions due to the empirical fast convergence rate under weak conditions. However, for problems such as X-ray computed tomography (CT) image reconstruction, where the inner least-squares problem is challenging and requires iterations, AL methods can be slow. This paper focuses on solving regularized (weighted) least-squares problems using a linearized variant of AL methods that replaces the quadratic AL penalty term in the scaled augmented Lagrangian with its separable quadratic surrogate (SQS) function, leading to a simpler ordered-subsets (OS) accelerable splitting-based algorithm, OS-LALM. To further accelerate the proposed algorithm, we use a second-order recursive system analysis to design a deterministic downward continuation approach that avoids tedious parameter tuning and provides fast convergence. Experimental results show that the proposed algorithm significantly accelerates the convergence of X-ray CT image reconstruction with negligible overhead and can reduce OS artifacts when using many subsets. PMID:25248178

  5. Sparse signal reconstruction from polychromatic X-ray CT measurements via mass attenuation discretization

    NASA Astrophysics Data System (ADS)

    Gu, Renliang; Dogandžić, Aleksandar

    2014-02-01

    We propose a method for reconstructing sparse images from polychromatic x-ray computed tomography (ct) measurements via mass attenuation coefficient discretization. The material of the inspected object and the incident spectrum are assumed to be unknown. We rewrite the Lambert-Beer's law in terms of integral expressions of mass attenuation and discretize the resulting integrals. We then present a penalized constrained least-squares optimization approach for reconstructing the underlying object from log-domain measurements, where an active set approach is employed to estimate incident energy density parameters and the nonnegativity and sparsity of the image density map are imposed using negative-energy and smooth ℓ1-norm penalty terms. We propose a two-step scheme for refining the mass attenuation discretization grid by using higher sampling rate over the range with higher photon energy, and eliminating the discretization points that have little effect on accuracy of the forward projection model. This refinement allows us to successfully handle the characteristic lines (Dirac impulses) in the incident energy density spectrum. We compare the proposed method with the standard filtered backprojection, which ignores the polychromatic nature of the measurements and sparsity of the image density map. Numerical simulations using both realistic simulated and real x-ray ct data are presented.

  6. Construction and analysis of a head CT-scan database for craniofacial reconstruction.

    PubMed

    Tilotta, Françoise; Richard, Frédéric; Glaunès, Joan; Berar, Maxime; Gey, Servane; Verdeille, Stéphane; Rozenholc, Yves; Gaudy, J F

    2009-10-30

    This paper is devoted to the construction of a complete database which is intended to improve the implementation and the evaluation of automated facial reconstruction. This growing database is currently composed of 85 head CT-scans of healthy European subjects aged 20-65 years old. It also includes the triangulated surfaces of the face and the skull of each subject. These surfaces are extracted from CT-scans using an original combination of image-processing techniques which are presented in the paper. Besides, a set of 39 referenced anatomical skull landmarks were located manually on each scan. Using the geometrical information provided by triangulated surfaces, we compute facial soft-tissue depths at each known landmark positions. We report the average thickness values at each landmark and compare our measures to those of the traditional charts of [J. Rhine, C.E. Moore, Facial Tissue Thickness of American Caucasoïds, Maxwell Museum of Anthropology, Albuquerque, New Mexico, 1982] and of several recent in vivo studies [M.H. Manhein, G.A. Listi, R.E. Barsley, et al., In vivo facial tissue depth measurements for children and adults, Journal of Forensic Sciences 45 (1) (2000) 48-60; S. De Greef, P. Claes, D. Vandermeulen, et al., Large-scale in vivo Caucasian facial soft tissue thickness database for craniofacial reconstruction, Forensic Science International 159S (2006) S126-S146; R. Helmer, Schödelidentifizierung durch elektronische bildmischung, Kriminalistik Verlag GmbH, Heidelberg, 1984].

  7. Fast X-ray CT image reconstruction using a linearized augmented Lagrangian method with ordered subsets.

    PubMed

    Nien, Hung; Fessler, Jeffrey A

    2015-02-01

    Augmented Lagrangian (AL) methods for solving convex optimization problems with linear constraints are attractive for imaging applications with composite cost functions due to the empirical fast convergence rate under weak conditions. However, for problems such as X-ray computed tomography (CT) image reconstruction, where the inner least-squares problem is challenging and requires iterations, AL methods can be slow. This paper focuses on solving regularized (weighted) least-squares problems using a linearized variant of AL methods that replaces the quadratic AL penalty term in the scaled augmented Lagrangian with its separable quadratic surrogate function, leading to a simpler ordered-subsets (OS) accelerable splitting-based algorithm, OS-LALM. To further accelerate the proposed algorithm, we use a second-order recursive system analysis to design a deterministic downward continuation approach that avoids tedious parameter tuning and provides fast convergence. Experimental results show that the proposed algorithm significantly accelerates the convergence of X-ray CT image reconstruction with negligible overhead and can reduce OS artifacts when using many subsets.

  8. Proximal ADMM for multi-channel image reconstruction in spectral X-ray CT.

    PubMed

    Sawatzky, Alex; Xu, Qiaofeng; Schirra, Carsten O; Anastasio, Mark A

    2014-08-01

    The development of spectral X-ray computed tomography (CT) using binned photon-counting detectors has received great attention in recent years and has enabled selective imaging of contrast agents loaded with K-edge materials. A practical issue in implementing this technique is the mitigation of the high-noise levels often present in material-decomposed sinogram data. In this work, the spectral X-ray CT reconstruction problem is formulated within a multi-channel (MC) framework in which statistical correlations between the decomposed material sinograms can be exploited to improve image quality. Specifically, a MC penalized weighted least squares (PWLS) estimator is formulated in which the data fidelity term is weighted by the MC covariance matrix and sparsity-promoting penalties are employed. This allows the use of any number of basis materials and is therefore applicable to photon-counting systems and K-edge imaging. To overcome numerical challenges associated with use of the full covariance matrix as a data fidelity weight, a proximal variant of the alternating direction method of multipliers is employed to minimize the MC PWLS objective function. Computer-simulation and experimental phantom studies are conducted to quantitatively evaluate the proposed reconstruction method.

  9. Peripheral pulmonary arteries: identification at multi-slice spiral CT with 3D reconstruction.

    PubMed

    Coche, Emmanuel; Pawlak, Sebastien; Dechambre, Stéphane; Maldague, Baudouin

    2003-04-01

    Our objective was to analyze the peripheral pulmonary arteries using thin-collimation multi-slice spiral CT. Twenty consecutive patients underwent enhanced-spiral multi-slice CT using 1-mm collimation. Two observers analyzed the pulmonary arteries by consensus on a workstation. Each artery was identified on axial and 3D shaded-surface display reconstruction images. Each subsegmental artery was measured at a mediastinal window setting and compared with anatomical classifications. The location and branching of every subsegmental artery was recorded. The number of well-visualized sub-subsegmental arteries at a mediastinal window setting was compared with those visualized at a lung window setting. Of 800 subsegmental arteries, 769 (96%) were correctly visualized and 123 accessory subsegmental arteries were identified using the mediastinal window setting. One thousand ninety-two of 2019 sub-subsegmental arteries (54%) identified using the lung window setting were correctly visualized using the mediastinal window setting. Enhanced multi-slice spiral CT with thin collimation can be used to analyze precisely the subsegmental pulmonary arteries and may identify even more distal pulmonary arteries.

  10. Accelerated barrier optimization compressed sensing (ABOCS) for CT reconstruction with improved convergence

    NASA Astrophysics Data System (ADS)

    Niu, Tianye; Ye, Xiaojing; Fruhauf, Quentin; Petrongolo, Michael; Zhu, Lei

    2014-04-01

    Recently, we proposed a new algorithm of accelerated barrier optimization compressed sensing (ABOCS) for iterative CT reconstruction. The previous implementation of ABOCS uses gradient projection (GP) with a Barzilai-Borwein (BB) step-size selection scheme (GP-BB) to search for the optimal solution. The algorithm does not converge stably due to its non-monotonic behavior. In this paper, we further improve the convergence of ABOCS using the unknown-parameter Nesterov (UPN) method and investigate the ABOCS reconstruction performance on clinical patient data. Comparison studies are carried out on reconstructions of computer simulation, a physical phantom and a head-and-neck patient. In all of these studies, the ABOCS results using UPN show more stable and faster convergence than those of the GP-BB method and a state-of-the-art Bregman-type method. As shown in the simulation study of the Shepp-Logan phantom, UPN achieves the same image quality as those of GP-BB and the Bregman-type methods, but reduces the iteration numbers by up to 50% and 90%, respectively. In the Catphan©600 phantom study, a high-quality image with relative reconstruction error (RRE) less than 3% compared to the full-view result is obtained using UPN with 17% projections (60 views). In the conventional filtered-backprojection reconstruction, the corresponding RRE is more than 15% on the same projection data. The superior performance of ABOCS with the UPN implementation is further demonstrated on the head-and-neck patient. Using 25% projections (91 views), the proposed method reduces the RRE from 21% as in the filtered backprojection (FBP) results to 7.3%. In conclusion, we propose UPN for ABOCS implementation. As compared to GP-BB and the Bregman-type methods, the new method significantly improves the convergence with higher stability and fewer iterations.

  11. Comparison of computational to human observer detection for evaluation of CT low dose iterative reconstruction

    NASA Astrophysics Data System (ADS)

    Eck, Brendan; Fahmi, Rachid; Brown, Kevin M.; Raihani, Nilgoun; Wilson, David L.

    2014-03-01

    Model observers were created and compared to human observers for the detection of low contrast targets in computed tomography (CT) images reconstructed with an advanced, knowledge-based, iterative image reconstruction method for low x-ray dose imaging. A 5-channel Laguerre-Gauss Hotelling Observer (CHO) was used with internal noise added to the decision variable (DV) and/or channel outputs (CO). Models were defined by parameters: (k1) DV-noise with standard deviation (std) proportional to DV std; (k2) DV-noise with constant std; (k3) CO-noise with constant std across channels; and (k4) CO-noise in each channel with std proportional to CO variance. Four-alternative forced choice (4AFC) human observer studies were performed on sub-images extracted from phantom images with and without a "pin" target. Model parameters were estimated using maximum likelihood comparison to human probability correct (PC) data. PC in human and all model observers increased with dose, contrast, and size, and was much higher for advanced iterative reconstruction (IMR) as compared to filtered back projection (FBP). Detection in IMR was better than FPB at 1/3 dose, suggesting significant dose savings. Model(k1,k2,k3,k4) gave the best overall fit to humans across independent variables (dose, size, contrast, and reconstruction) at fixed display window. However Model(k1) performed better when considering model complexity using the Akaike information criterion. Model(k1) fit the extraordinary detectability difference between IMR and FBP, despite the different noise quality. It is anticipated that the model observer will predict results from iterative reconstruction methods having similar noise characteristics, enabling rapid comparison of methods.

  12. Accelerated barrier optimization compressed sensing (ABOCS) for CT reconstruction with improved convergence

    PubMed Central

    Niu, Tianye; Ye, Xiaojing; Fruhauf, Quentin; Petrongolo, Michael; Zhu, Lei

    2014-01-01

    Recently, we proposed a new algorithm of accelerated barrier optimization compressed sensing (ABOCS) for iterative CT reconstruction. The previous implementation of ABOCS uses gradient projection (GP) with a Barzilai-Borwein (BB) step-size selection scheme (GP-BB) to search for the optimal solution. The algorithm does not converge stably due to its non-monotonic behavior. In this paper, we further improve the convergence of ABOCS using the unknown-parameter Nesterov (UPN) method and investigate the ABOCS reconstruction performance on clinical patient data. Comparison studies are carried out on reconstructions of computer simulation, a physical phantom and a head-and-neck patient. In all of these studies, the ABOCS results using UPN show more stable and faster convergence than those of the GPBB method and a state-of-the-art Bregman-type method. As shown in the simulation study of the Shepp-Logan phantom, UPN achieves the same image quality as those of GPBB and the Bregman-type method, but reduces the iteration numbers by up to 50% and 90%, respectively. In the Catphan©600 phantom study, a high-quality image with relative reconstruction error (RRE) less than 3% compared to the full-view result is obtained using UPN with 17% projections (60 views). In the conventional filtered-backprojection (FBP) reconstruction, the corresponding RRE is more than 15% on the same projection data. The superior performance of ABOCS with the UPN implementation is further demonstrated on the head-and-neck patient. Using 25% projections (91 views), the proposed method reduces the RRE from 21% as in the FBP results to 7.3%. In conclusion, we propose UPN for ABOCS implementation. As compared to GPBB and the Bregman-type methods, the new method significantly improves the convergence with higher stability and less iterations. PMID:24625411

  13. Investigation of a one-step spectral CT reconstruction algorithm for direct inversion into basis material images

    NASA Astrophysics Data System (ADS)

    Gilat Schmidt, Taly; Sidky, Emil Y.

    2015-03-01

    Photon-counting detectors with pulse-height analysis have shown promise for improved spectral CT imaging. This study investigated a novel spectral CT reconstruction method that directly estimates basis-material images from the measured energy-bin data (i.e., `one-step' reconstruction). The proposed algorithm can incorporate constraints to stabilize the reconstruction and potentially reduce noise. The algorithm minimizes the error between the measured energy-bin data and the data estimated from the reconstructed basis images. A total variation (TV) constraint was also investigated for additional noise reduction. The proposed one-step algorithm was applied to simulated data of an anthropomorphic phantom with heterogeneous tissue composition. Reconstructed water, bone, and gadolinium basis images were compared for the proposed one-step algorithm and the conventional `two-step' method of decomposition followed by reconstruction. The unconstrained algorithm provided a 30% to 60% reduction in noise standard deviation compared to the two-step algorithm. The fTV =0.8 constraint provided a small reduction in noise (˜ 1%) compared to the unconstrained reconstruction. Images reconstructed with the fTV =0.5 constraint demonstrated 77% to 94% standard deviation reduction compared to the two-step reconstruction, however with increased blurring. There were no significant differences in the mean values reconstructed by the investigated algorithms. Overall, the proposed one-step spectral CT reconstruction algorithm provided three-material-decomposition basis images with reduced noise compared to the conventional two-step approach. When using a moderate TV constraint factor (fTV = 0.8), a 30%-60% reduction in noise standard deviation was achieved while preserving the edge profile for this simulated phantom.

  14. Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability

    PubMed Central

    Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

    2016-01-01

    Purpose To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Methods Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Results Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Conclusions Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features. PMID:27741289

  15. Reconstruction-plane-dependent weighted FDK algorithm for cone beam volumetric CT

    NASA Astrophysics Data System (ADS)

    Tang, Xiangyang; Hsieh, Jiang

    2005-04-01

    The original FDK algorithm has been extensively employed in medical and industrial imaging applications. With an increased cone angle, cone beam (CB) artifacts in images reconstructed by the original FDK algorithm deteriorate, since the circular trajectory does not satisfy the so-called data sufficiency condition (DSC). A few "circular plus" trajectories have been proposed in the past to reduce CB artifacts by meeting the DSC. However, the circular trajectory has distinct advantages over other scanning trajectories in practical CT imaging, such as cardiac, vascular and perfusion applications. In addition to looking into the DSC, another insight into the CB artifacts of the original FDK algorithm is the inconsistency between conjugate rays that are 180° apart in view angle. The inconsistence between conjugate rays is pixel dependent, i.e., it varies dramatically over pixels within the image plane to be reconstructed. However, the original FDK algorithm treats all conjugate rays equally, resulting in CB artifacts that can be avoided if appropriate view weighting strategy is exercised. In this paper, a modified FDK algorithm is proposed, along with an experimental evaluation and verification, in which the helical body phantom and a humanoid head phantom scanned by a volumetric CT (64 x 0.625 mm) are utilized. Without extra trajectories supplemental to the circular trajectory, the modified FDK algorithm applies reconstruction-plane-dependent view weighting on projection data before 3D backprojection, which reduces the inconsistency between conjugate rays by suppressing the contribution of one of the conjugate rays with a larger cone angle. Both computer-simulated and real phantom studies show that, up to a moderate cone angle, the CB artifacts can be substantially suppressed by the modified FDK algorithm, while advantages of the original FDK algorithm, such as the filtered backprojection algorithm structure, 1D ramp filtering, and data manipulation efficiency, can be

  16. Mapping the nasal airways: using histology to enhance CT-based three-dimensional reconstruction in Nycticebus.

    PubMed

    Deleon, Valerie Burke; Smith, Timothy D

    2014-11-01

    Three-dimensional reconstructions of imaging data are an increasingly common approach for studying anatomical structure. However, certain aspects of anatomy, including microscopic structure and differentiating tissue types, continue to benefit from traditional histological analyses. We present here a detailed methodology for combining data from microCT and histological imaging to create 3D virtual reconstructions for visualization and further analyses. We used this approach to study the distribution of olfactory mucosa on ethmoturbinal I of an adult pygmy slow loris, Nycticebus pygmaeus. MicroCT imaging of the specimen was followed by processing, embedding, and sectioning for histological analysis. We identified corresponding features in the CT and histological data, and used these to reconstruct the plane of section in the CT volume. The CT volume was then digitally re-sliced, such that orthogonal sections of the CT image corresponded to histological sections. Histological images were annotated for the features of interest (in this case, the contour of soft tissue on ethmoturbinal I and the extent of olfactory mucosa), and annotations were transferred to binary masks in the CT volume. These masks were combined with density-based surface reconstructions of the skull to create an enhanced 3D virtual reconstruction, in which the bony surfaces are coded for mucosal function. We identified a series of issues that may be raised in this approach, for example, deformation related to histological processing, and we make recommendations for addressing these issues. This method provides an evidence-based approach to 3D visualization and analysis of microscopic features in an anatomic context.

  17. Effect of reconstruction algorithms on the accuracy of 99mTc sestamibi SPECT/CT parathyroid imaging

    PubMed Central

    Nichols, Kenneth J; Tronco, Gene G; Palestro, Christopher J

    2015-01-01

    The superiority of SPECT/CT over SPECT for 99mTc-sestamibi parathyroid imaging often is assumed to be due to improved lesion localization provided by the anatomic component (computed tomography) of the examination. It also is possible that this superiority may be related to the algorithms used for SPECT data reconstruction. The objective of this investigation was to determine the effect of SPECT reconstruction algorithms on the accuracy of MIBI SPECT/CT parathyroid imaging. We retrospectively analyzed preoperative MIBI SPECT/CT parathyroid imaging studies performed on 106 patients. SPECT data were reconstructed by filtered back projection (FBP) and by iterative reconstruction with corrections for collimator resolution recovery and attenuation (IRC). Two experienced readers independently graded lesion detection certainty on a 5-point scale without knowledge of each other’s readings, reconstruction methods, other test results or final diagnoses. All patients had surgical confirmation of the final diagnosis, including disease limited to the neck, and location and weight of excised lesion(s). There were 135 parathyroid lesions among the 106 patients. For FBP SPECT/CT and IRC SPECT/CT sensitivity was 76% and 90% (p = 0.003), specificity was 87% and 87% (p = 0.90), and accuracy was 83% and 88% (p = 0.04), respectively. Inter-rater agreement was significantly higher for IRC than for FBP (kappa = 0.76, “good agreement”, versus kappa = 0.58, “moderate agreement”, p < 0.0001). We conclude that the improved accuracy of MIBI SPECT/CT compared to MIBI SPECT for preoperative parathyroid lesion localization is due in part to the use of IRC for SPECT data reconstruction. PMID:25973340

  18. Task-driven image acquisition and reconstruction in cone-beam CT.

    PubMed

    Gang, Grace J; Stayman, J Webster; Ehtiati, Tina; Siewerdsen, Jeffrey H

    2015-04-21

    This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ± 30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the tilt

  19. Task-driven image acquisition and reconstruction in cone-beam CT

    PubMed Central

    Gang, Grace J.; Stayman, J. Webster; Ehtiati, Tina; Siewerdsen, Jeffrey H.

    2015-01-01

    This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters and in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ±30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e., the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the

  20. Task-driven image acquisition and reconstruction in cone-beam CT

    NASA Astrophysics Data System (ADS)

    Gang, Grace J.; Webster Stayman, J.; Ehtiati, Tina; Siewerdsen, Jeffrey H.

    2015-04-01

    This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d‧) is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ±30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d‧ for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d‧ by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the

  1. Potential of combining iterative reconstruction with noise efficient detector design: aggressive dose reduction in head CT

    PubMed Central

    Bender, B; Schabel, C; Fenchel, M; Ernemann, U; Korn, A

    2015-01-01

    Objective: With further increase of CT numbers and their dominant contribution to medical exposure, there is a recent quest for more effective dose control. While reintroduction of iterative reconstruction (IR) has proved its potential in many applications, a novel focus is placed on more noise efficient detectors. Our purpose was to assess the potential of IR in combination with an integrated circuit detector (ICD) for aggressive dose reduction in head CT. Methods: Non-contrast low-dose head CT [190 mAs; weighted volume CT dose index (CTDIvol), 33.2 mGy] was performed in 50 consecutive patients, using a new noise efficient detector and IR. Images were assessed in terms of quantitative and qualitative image quality and compared with standard dose acquisitions (320 mAs; CTDIvol, 59.7 mGy) using a conventional detector and filtered back projection. Results: By combining ICD and IR in low-dose examinations, the signal to noise was improved by about 13% above the baseline level in the standard-dose control group. Both, contrast-to-noise ratio (2.02 ± 0.6 vs 1.88 ± 0.4; p = 0.18) and objective measurements of image sharpness (695 ± 84 vs 705 ± 151 change in Hounsfield units per pixel; p = 0.79) were fully preserved in the low-dose group. Likewise, there was no significant difference in the grading of several subjective image quality parameters when both noise-reducing strategies were used in low-dose examinations. Conclusion: Combination of noise efficient detector with IR allows for meaningful dose reduction in head CT without compromise of standard image quality. Advances in knowledge: Our study demonstrates the feasibility of almost 50% dose reduction in head CT dose (1.1 mSv per scan) through combination of novel dose-reducing strategies. PMID:25827204

  2. Coronary artery calcium score: influence of reconstruction interval at 16-detector row CT with retrospective electrocardiographic gating.

    PubMed

    Schlosser, Thomas; Hunold, Peter; Schmermund, Axel; Kühl, Hilmar; Waltering, Kai-Uwe; Debatin, Jörg F; Barkhausen, Jörg

    2004-11-01

    In 30 patients, Agatston and volumetric scores were assessed by using retrospectively gated multi-detector row computed tomography (CT). For each patient, 10 data sets were created at different times and were evenly spaced throughout the cardiac cycle. For each reconstruction, patients were assigned a percentile that described the level of cardiovascular risk. Nineteen (63%) of 30 patients could be assigned to more than one risk group depending on the reconstruction interval used. Agatston and volumetric scores both proved highly dependent on the reconstruction interval used (coefficient of variation, < or =63.1%) even with the most advanced CT scanners. Accurate and reproducible quantification of coronary calcium seems to require analysis of multiple reconstructions.

  3. Iterative CT reconstruction on limited angle trajectories applied to robotic inspection

    NASA Astrophysics Data System (ADS)

    Banjak, H.; Costin, M.; Vienne, C.; Guillamet, R.; Kaftandjian, V.

    2017-02-01

    Robotic inspection is one of the acknowledged new trends in X-ray Non Destructive testing (NDT) since it allows more flexibility in the acquisition trajectory and therefore a valued adaptability to object and environment constraints. In this context, we are developing an advanced Computed Tomography (CT) robotic platform consisting of two robots equipped, with a micro-focus X-ray tube and a flat panel detector, respectively. In parallel to the equipment installation, we propose to address the new challenges brought by this robotic inspection. In particular we focus on 3D iterative reconstruction algorithms that deal with few and limited-angle data. For this purpose, we consider regularized algebraic methods. In particular, we propose two algorithms named SART-FISTA-TV and DART-FISTA-TV. The first one is based on the common used SART [1] algorithm and the second is based on Discrete Algebraic Reconstruction Technique (DART) [2] which is an algebraic algorithm that incorporates prior knowledge about the different materials (attenuation coefficient) of the scanned object into the reconstruction process. The two proposed algorithms use Total Variation (TV) regularization and Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) to increase the convergence speed. For performance evaluation, we illustrate a numerical comparison of these algorithms from both complete (noiseless and noisy) and truncated data generated on a reverse helix of angular range limited to 150 degrees. CIVA [3] software is used to simulate these projection data. We also show reconstruction results using the robotic inspection platform with a view angle limited to 150 degrees and a reduced number of projections.

  4. Scattered radiation in flat-detector based cone-beam CT: propagation of signal, contrast, and noise into reconstructed volumes

    NASA Astrophysics Data System (ADS)

    Wiegert, Jens; Hohmann, Steffen; Bertram, Matthias

    2007-03-01

    This paper presents a novel framework for the systematic assessment of the impact of scattered radiation in .at-detector based cone-beam CT. While it is well known that scattered radiation causes three di.erent types of artifacts in reconstructed images (inhomogeneity artifacts such as cupping and streaks, degradation of contrast, and enhancement of noise), investigations in the literature quantify the impact of scatter mostly only in terms of inhomogeneity artifacts, giving little insight, e.g., into the visibility of low contrast lesions. Therefore, for this study a novel framework has been developed that in addition to normal reconstruction of the CT (HU) number allows for reconstruction of voxelized expectation values of three additional important characteristics of image quality: signal degradation, contrast reduction, and noise variances. The new framework has been applied to projection data obtained with voxelized Monte-Carlo simulations of clinical CT data sets of high spatial resolution. Using these data, the impact of scattered radiation was thoroughly studied for realistic and clinically relevant patient geometries of the head, thorax, and pelvis region. By means of spatially resolved reconstructions of contrast and noise propagation, the image quality of a scenario with using standard antiscatter grids could be evaluated with great detail. Results show the spatially resolved contrast degradation and the spatially resolved expected standard deviation of the noise at any position in the reconstructed object. The new framework represents a general tool for analyzing image quality in reconstructed images.

  5. Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment

    PubMed Central

    Meng, Bowen; Pratx, Guillem; Xing, Lei

    2011-01-01

    Purpose: Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT/CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment. Methods: In this work, we accelerated the Feldcamp–Davis–Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT/CT reconstruction algorithm. Results: Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10−7. Our study also proved that cloud computing with MapReduce is fault tolerant: the

  6. Contrast adaptive total p-norm variation minimization approach to CT reconstruction for artifact reduction in reduced-view brain perfusion CT

    NASA Astrophysics Data System (ADS)

    Kim, Chang-Won; Kim, Jong-Hyo

    2011-03-01

    Perfusion CT (PCT) examinations are getting more frequently used for diagnosis of acute brain diseases such as hemorrhage and infarction, because the functional map images it produces such as regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), and mean transit time (MTT) may provide critical information in the emergency work-up of patient care. However, a typical PCT scans the same slices several tens of times after injection of contrast agent, which leads to much increased radiation dose and is inevitability of growing concern for radiation-induced cancer risk. Reducing the number of views in projection in combination of TV minimization reconstruction technique is being regarded as an option for radiation reduction. However, reconstruction artifacts due to insufficient number of X-ray projections become problematic especially when high contrast enhancement signals are present or patient's motion occurred. In this study, we present a novel reconstruction technique using contrast-adaptive TpV minimization that can reduce reconstruction artifacts effectively by using different p-norms in high contrast and low contrast objects. In the proposed method, high contrast components are first reconstructed using thresholded projection data and low p-norm total variation to reflect sparseness in both projection and reconstruction spaces. Next, projection data are modified to contain only low contrast objects by creating projection data of reconstructed high contrast components and subtracting them from original projection data. Then, the low contrast projection data are reconstructed by using relatively high p-norm TV minimization technique, and are combined with the reconstructed high contrast component images to produce final reconstructed images. The proposed algorithm was applied to numerical phantom and a clinical data set of brain PCT exam, and the resultant images were compared with those using filtered back projection (FBP) and conventional TV

  7. Multiresolution iterative reconstruction in high-resolution extremity cone-beam CT

    NASA Astrophysics Data System (ADS)

    Cao, Qian; Zbijewski, Wojciech; Sisniega, Alejandro; Yorkston, John; Siewerdsen, Jeffrey H.; Webster Stayman, J.

    2016-10-01

    Application of model-based iterative reconstruction (MBIR) to high resolution cone-beam CT (CBCT) is computationally challenging because of the very fine discretization (voxel size  <100 µm) of the reconstructed volume. Moreover, standard MBIR techniques require that the complete transaxial support for the acquired projections is reconstructed, thus precluding acceleration by restricting the reconstruction to a region-of-interest. To reduce the computational burden of high resolution MBIR, we propose a multiresolution penalized-weighted least squares (PWLS) algorithm, where the volume is parameterized as a union of fine and coarse voxel grids as well as selective binning of detector pixels. We introduce a penalty function designed to regularize across the boundaries between the two grids. The algorithm was evaluated in simulation studies emulating an extremity CBCT system and in a physical study on a test-bench. Artifacts arising from the mismatched discretization of the fine and coarse sub-volumes were investigated. The fine grid region was parameterized using 0.15 mm voxels and the voxel size in the coarse grid region was varied by changing a downsampling factor. No significant artifacts were found in either of the regions for downsampling factors of up to 4×. For a typical extremities CBCT volume size, this downsampling corresponds to an acceleration of the reconstruction that is more than five times faster than a brute force solution that applies fine voxel parameterization to the entire volume. For certain configurations of the coarse and fine grid regions, in particular when the boundary between the regions does not cross high attenuation gradients, downsampling factors as high as 10×  can be used without introducing artifacts, yielding a ~50×  speedup in PWLS. The proposed multiresolution algorithm significantly reduces the computational burden of high resolution iterative CBCT reconstruction and can be extended to other applications of

  8. First 3D reconstruction of the rhizocephalan root system using MicroCT

    NASA Astrophysics Data System (ADS)

    Noever, Christoph; Keiler, Jonas; Glenner, Henrik

    2016-07-01

    Parasitic barnacles (Cirripedia: Rhizocephala) are highly specialized parasites of crustaceans. Instead of an alimentary tract for feeding they utilize a system of roots, which infiltrates the body of their hosts to absorb nutrients. Using X-ray micro computer tomography (MicroCT) and computer-aided 3D-reconstruction, we document the spatial organization of this root system, the interna, inside the intact host and also demonstrate its use for morphological examinations of the parasites reproductive part, the externa. This is the first 3D visualization of the unique root system of the Rhizocephala in situ, showing how it is related to the inner organs of the host. We investigated the interna from different parasitic barnacles of the family Peltogastridae, which are parasitic on anomuran crustaceans. Rhizocephalan parasites of pagurid hermit crabs and lithodid crabs were analysed in this study.

  9. SU-E-J-218: Evaluation of CT Images Created Using a New Metal Artifact Reduction Reconstruction Algorithm for Radiation Therapy Treatment Planning

    SciTech Connect

    Niemkiewicz, J; Palmiotti, A; Miner, M; Stunja, L; Bergene, J

    2014-06-01

    Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU values were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken of the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation

  10. Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction

    NASA Astrophysics Data System (ADS)

    Wang, Adam S.; Webster Stayman, J.; Otake, Yoshito; Kleinszig, Gerhard; Vogt, Sebastian; Gallia, Gary L.; Khanna, A. Jay; Siewerdsen, Jeffrey H.

    2014-02-01

    The potential for statistical image reconstruction methods such as penalized-likelihood (PL) to improve C-arm cone-beam CT (CBCT) soft-tissue visualization for intraoperative imaging over conventional filtered backprojection (FBP) is assessed in this work by making a fair comparison in relation to soft-tissue performance. A prototype mobile C-arm was used to scan anthropomorphic head and abdomen phantoms as well as a cadaveric torso at doses substantially lower than typical values in diagnostic CT, and the effects of dose reduction via tube current reduction and sparse sampling were also compared. Matched spatial resolution between PL and FBP was determined by the edge spread function of low-contrast (˜40-80 HU) spheres in the phantoms, which were representative of soft-tissue imaging tasks. PL using the non-quadratic Huber penalty was found to substantially reduce noise relative to FBP, especially at lower spatial resolution where PL provides a contrast-to-noise ratio increase up to 1.4-2.2× over FBP at 50% dose reduction across all objects. Comparison of sampling strategies indicates that soft-tissue imaging benefits from fully sampled acquisitions at dose above ˜1.7 mGy and benefits from 50% sparsity at dose below ˜1.0 mGy. Therefore, an appropriate sampling strategy along with the improved low-contrast visualization offered by statistical reconstruction demonstrates the potential for extending intraoperative C-arm CBCT to applications in soft-tissue interventions in neurosurgery as well as thoracic and abdominal surgeries by overcoming conventional tradeoffs in noise, spatial resolution, and dose.

  11. Regularization design for high-quality cone-beam CT of intracranial hemorrhage using statistical reconstruction

    NASA Astrophysics Data System (ADS)

    Dang, H.; Stayman, J. W.; Xu, J.; Sisniega, A.; Zbijewski, W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

    2016-03-01

    Intracranial hemorrhage (ICH) is associated with pathologies such as hemorrhagic stroke and traumatic brain injury. Multi-detector CT is the current front-line imaging modality for detecting ICH (fresh blood contrast 40-80 HU, down to 1 mm). Flat-panel detector (FPD) cone-beam CT (CBCT) offers a potential alternative with a smaller scanner footprint, greater portability, and lower cost potentially well suited to deployment at the point of care outside standard diagnostic radiology and emergency room settings. Previous studies have suggested reliable detection of ICH down to 3 mm in CBCT using high-fidelity artifact correction and penalized weighted least-squared (PWLS) image reconstruction with a post-artifact-correction noise model. However, ICH reconstructed by traditional image regularization exhibits nonuniform spatial resolution and noise due to interaction between the statistical weights and regularization, which potentially degrades the detectability of ICH. In this work, we propose three regularization methods designed to overcome these challenges. The first two compute spatially varying certainty for uniform spatial resolution and noise, respectively. The third computes spatially varying regularization strength to achieve uniform "detectability," combining both spatial resolution and noise in a manner analogous to a delta-function detection task. Experiments were conducted on a CBCT test-bench, and image quality was evaluated for simulated ICH in different regions of an anthropomorphic head. The first two methods improved the uniformity in spatial resolution and noise compared to traditional regularization. The third exhibited the highest uniformity in detectability among all methods and best overall image quality. The proposed regularization provides a valuable means to achieve uniform image quality in CBCT of ICH and is being incorporated in a CBCT prototype for ICH imaging.

  12. Alternating dual updates algorithm for X-ray CT reconstruction on the GPU

    PubMed Central

    McGaffin, Madison G.; Fessler, Jeffrey A.

    2015-01-01

    Model-based image reconstruction (MBIR) for X-ray computed tomography (CT) offers improved image quality and potential low-dose operation, but has yet to reach ubiquity in the clinic. MBIR methods form an image by solving a large statistically motivated optimization problem, and the long time it takes to numerically solve this problem has hampered MBIR’s adoption. We present a new optimization algorithm for X-ray CT MBIR based on duality and group coordinate ascent that may converge even with approximate updates and can handle a wide range of regularizers, including total variation (TV). The algorithm iteratively updates groups of dual variables corresponding to terms in the cost function; these updates are highly parallel and map well onto the GPU. Although the algorithm stores a large number of variables, the “working size” for each of the algorithm’s steps is small and can be efficiently streamed to the GPU while other calculations are being performed. The proposed algorithm converges rapidly on both real and simulated data and shows promising parallelization over multiple devices. PMID:26878031

  13. Acoustic property reconstruction of a neonate Yangtze finless porpoise's (Neophocaena asiaeorientalis) head based on CT imaging.

    PubMed

    Wei, Chong; Wang, Zhitao; Song, Zhongchang; Wang, Kexiong; Wang, Ding; Au, Whitlow W L; Zhang, Yu

    2015-01-01

    The reconstruction of the acoustic properties of a neonate finless porpoise's head was performed using X-ray computed tomography (CT). The head of the deceased neonate porpoise was also segmented across the body axis and cut into slices. The averaged sound velocity and density were measured, and the Hounsfield units (HU) of the corresponding slices were obtained from computed tomography scanning. A regression analysis was employed to show the linear relationships between the Hounsfield unit and both sound velocity and density of samples. Furthermore, the CT imaging data were used to compare the HU value, sound velocity, density and acoustic characteristic impedance of the main tissues in the porpoise's head. The results showed that the linear relationships between HU and both sound velocity and density were qualitatively consistent with previous studies on Indo-pacific humpback dolphins and Cuvier's beaked whales. However, there was no significant increase of the sound velocity and acoustic impedance from the inner core to the outer layer in this neonate finless porpoise's melon.

  14. 4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

    NASA Astrophysics Data System (ADS)

    Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

    2016-02-01

    A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp-Davis-Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations.

  15. Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction

    NASA Technical Reports Server (NTRS)

    Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

    2000-01-01

    This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

  16. 4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

    PubMed Central

    Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

    2016-01-01

    A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp–Davis–Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations. PMID:26758496

  17. An Efficient Augmented Lagrangian Method for Statistical X-Ray CT Image Reconstruction

    PubMed Central

    Li, Jiaojiao; Niu, Shanzhou; Huang, Jing; Bian, Zhaoying; Feng, Qianjin; Yu, Gaohang; Liang, Zhengrong; Chen, Wufan; Ma, Jianhua

    2015-01-01

    Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement. However, due to the nonlinear expression of the objective function, most exiting algorithms related to the SIR unavoidably suffer from heavy computation load and slow convergence rate, especially when an edge-preserving or sparsity-based penalty or regularization is incorporated. In this work, to address abovementioned issues of the general algorithms related to the SIR, we propose an adaptive nonmonotone alternating direction algorithm in the framework of augmented Lagrangian multiplier method, which is termed as “ALM-ANAD”. The algorithm effectively combines an alternating direction technique with an adaptive nonmonotone line search to minimize the augmented Lagrangian function at each iteration. To evaluate the present ALM-ANAD algorithm, both qualitative and quantitative studies were conducted by using digital and physical phantoms. Experimental results show that the present ALM-ANAD algorithm can achieve noticeable gains over the classical nonlinear conjugate gradient algorithm and state-of-the-art split Bregman algorithm in terms of noise reduction, contrast-to-noise ratio, convergence rate, and universal quality index metrics. PMID:26495975

  18. Supervised recursive segmentation of volumetric CT images for 3D reconstruction of lung and vessel tree.

    PubMed

    Li, Xuanping; Wang, Xue; Dai, Yixiang; Zhang, Pengbo

    2015-12-01

    Three dimensional reconstruction of lung and vessel tree has great significance to 3D observation and quantitative analysis for lung diseases. This paper presents non-sheltered 3D models of lung and vessel tree based on a supervised semi-3D lung tissues segmentation method. A recursive strategy based on geometric active contour is proposed instead of the "coarse-to-fine" framework in existing literature to extract lung tissues from the volumetric CT slices. In this model, the segmentation of the current slice is supervised by the result of the previous one slice due to the slight changes between adjacent slice of lung tissues. Through this mechanism, lung tissues in all the slices are segmented fast and accurately. The serious problems of left and right lungs fusion, caused by partial volume effects, and segmentation of pleural nodules can be settled meanwhile during the semi-3D process. The proposed scheme is evaluated by fifteen scans, from eight healthy participants and seven participants suffering from early-stage lung tumors. The results validate the good performance of the proposed method compared with the "coarse-to-fine" framework. The segmented datasets are utilized to reconstruct the non-sheltered 3D models of lung and vessel tree.

  19. CT performance as a variable function of resolution, noise, and task property for iterative reconstructions

    NASA Astrophysics Data System (ADS)

    Chen, Baiyu; Richard, Samuel; Christianson, Olav; Zhou, Xiaodong; Samei, Ehsan

    2012-03-01

    The increasing availability of iterative reconstruction (IR) algorithms on clinical scanners is creating a demand for effectively and efficiently evaluating imaging performance and potential dose reduction. In this study, the location- and task-specific evaluation was performed using detectability index (d') by combining a task function, the task transfer function (TTF), and the noise power spectrum (NPS). Task function modeled a wide variety detection tasks in terms of shape and contrast. The TTF and NPS were measured from a physical phantom as a function of contrast and dose levels. Measured d' values were compared between three IRs (IRIS, SAFIRE3 and SAFIRE5) and conventional filtered back-projection (FBP) at various dose levels, showing an equivalent performance of IR at lower dose levels. AUC further calculated from d' showed that compared to FBP, SAFIRE5 may reduce dose by up to 50-60%; SAFIRE3 and IRIS by up to 20-30%. This study provides an initial framework for the localized and task-specific evaluation of IRs in CT and a guideline for the identification of optimal operating dose point with iterative reconstructions.

  20. Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

    SciTech Connect

    Stassi, D.; Ma, H.; Schmidt, T. G.; Dutta, S.; Soderman, A.; Pazzani, D.; Gros, E.; Okerlund, D.

    2016-01-15

    Purpose: Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. Methods: An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three

  1. Improved compressed sensing-based cone-beam CT reconstruction using adaptive prior image constraints

    NASA Astrophysics Data System (ADS)

    Lee, Ho; Xing, Lei; Davidi, Ran; Li, Ruijiang; Qian, Jianguo; Lee, Rena

    2012-04-01

    Volumetric cone-beam CT (CBCT) images are acquired repeatedly during a course of radiation therapy and a natural question to ask is whether CBCT images obtained earlier in the process can be utilized as prior knowledge to reduce patient imaging dose in subsequent scans. The purpose of this work is to develop an adaptive prior image constrained compressed sensing (APICCS) method to solve this problem. Reconstructed images using full projections are taken on the first day of radiation therapy treatment and are used as prior images. The subsequent scans are acquired using a protocol of sparse projections. In the proposed APICCS algorithm, the prior images are utilized as an initial guess and are incorporated into the objective function in the compressed sensing (CS)-based iterative reconstruction process. Furthermore, the prior information is employed to detect any possible mismatched regions between the prior and current images for improved reconstruction. For this purpose, the prior images and the reconstructed images are classified into three anatomical regions: air, soft tissue and bone. Mismatched regions are identified by local differences of the corresponding groups in the two classified sets of images. A distance transformation is then introduced to convert the information into an adaptive voxel-dependent relaxation map. In constructing the relaxation map, the matched regions (unchanged anatomy) between the prior and current images are assigned with smaller weight values, which are translated into less influence on the CS iterative reconstruction process. On the other hand, the mismatched regions (changed anatomy) are associated with larger values and the regions are updated more by the new projection data, thus avoiding any possible adverse effects of prior images. The APICCS approach was systematically assessed by using patient data acquired under standard and low-dose protocols for qualitative and quantitative comparisons. The APICCS method provides an

  2. MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

    SciTech Connect

    Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J

    2015-06-15

    Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features.

  3. Acceleration of fluoro-CT reconstruction for a mobile C-Arm on GPU and FPGA hardware: a simulation study

    NASA Astrophysics Data System (ADS)

    Xue, Xinwei; Cheryauka, Arvi; Tubbs, David

    2006-03-01

    CT imaging in interventional and minimally-invasive surgery requires high-performance computing solutions that meet operational room demands, healthcare business requirements, and the constraints of a mobile C-arm system. The computational requirements of clinical procedures using CT-like data are increasing rapidly, mainly due to the need for rapid access to medical imagery during critical surgical procedures. The highly parallel nature of Radon transform and CT algorithms enables embedded computing solutions utilizing a parallel processing architecture to realize a significant gain of computational intensity with comparable hardware and program coding/testing expenses. In this paper, using a sample 2D and 3D CT problem, we explore the programming challenges and the potential benefits of embedded computing using commodity hardware components. The accuracy and performance results obtained on three computational platforms: a single CPU, a single GPU, and a solution based on FPGA technology have been analyzed. We have shown that hardware-accelerated CT image reconstruction can be achieved with similar levels of noise and clarity of feature when compared to program execution on a CPU, but gaining a performance increase at one or more orders of magnitude faster. 3D cone-beam or helical CT reconstruction and a variety of volumetric image processing applications will benefit from similar accelerations.

  4. Evaluation of robustness of maximum likelihood cone-beam CT reconstruction with total variation regularization.

    PubMed

    Stsepankou, D; Arns, A; Ng, S K; Zygmanski, P; Hesser, J

    2012-10-07

    The objective of this paper is to evaluate an iterative maximum likelihood (ML) cone-beam computed tomography (CBCT) reconstruction with total variation (TV) regularization with respect to the robustness of the algorithm due to data inconsistencies. Three different and (for clinical application) typical classes of errors are considered for simulated phantom and measured projection data: quantum noise, defect detector pixels and projection matrix errors. To quantify those errors we apply error measures like mean square error, signal-to-noise ratio, contrast-to-noise ratio and streak indicator. These measures are derived from linear signal theory and generalized and applied for nonlinear signal reconstruction. For quality check, we focus on resolution and CT-number linearity based on a Catphan phantom. All comparisons are made versus the clinical standard, the filtered backprojection algorithm (FBP). In our results, we confirm and substantially extend previous results on iterative reconstruction such as massive undersampling of the number of projections. Errors of projection matrix parameters of up to 1° projection angle deviations are still in the tolerance level. Single defect pixels exhibit ring artifacts for each method. However using defect pixel compensation, allows up to 40% of defect pixels for passing the standard clinical quality check. Further, the iterative algorithm is extraordinarily robust in the low photon regime (down to 0.05 mAs) when compared to FPB, allowing for extremely low-dose image acquisitions, a substantial issue when considering daily CBCT imaging for position correction in radiotherapy. We conclude that the ML method studied herein is robust under clinical quality assurance conditions. Consequently, low-dose regime imaging, especially for daily patient localization in radiation therapy is possible without change of the current hardware of the imaging system.

  5. Evaluation of robustness of maximum likelihood cone-beam CT reconstruction with total variation regularization

    NASA Astrophysics Data System (ADS)

    Stsepankou, D.; Arns, A.; Ng, S. K.; Zygmanski, P.; Hesser, J.

    2012-10-01

    The objective of this paper is to evaluate an iterative maximum likelihood (ML) cone-beam computed tomography (CBCT) reconstruction with total variation (TV) regularization with respect to the robustness of the algorithm due to data inconsistencies. Three different and (for clinical application) typical classes of errors are considered for simulated phantom and measured projection data: quantum noise, defect detector pixels and projection matrix errors. To quantify those errors we apply error measures like mean square error, signal-to-noise ratio, contrast-to-noise ratio and streak indicator. These measures are derived from linear signal theory and generalized and applied for nonlinear signal reconstruction. For quality check, we focus on resolution and CT-number linearity based on a Catphan phantom. All comparisons are made versus the clinical standard, the filtered backprojection algorithm (FBP). In our results, we confirm and substantially extend previous results on iterative reconstruction such as massive undersampling of the number of projections. Errors of projection matrix parameters of up to 1° projection angle deviations are still in the tolerance level. Single defect pixels exhibit ring artifacts for each method. However using defect pixel compensation, allows up to 40% of defect pixels for passing the standard clinical quality check. Further, the iterative algorithm is extraordinarily robust in the low photon regime (down to 0.05 mAs) when compared to FPB, allowing for extremely low-dose image acquisitions, a substantial issue when considering daily CBCT imaging for position correction in radiotherapy. We conclude that the ML method studied herein is robust under clinical quality assurance conditions. Consequently, low-dose regime imaging, especially for daily patient localization in radiation therapy is possible without change of the current hardware of the imaging system.

  6. Model-based Iterative Reconstruction: Effect on Patient Radiation Dose and Image Quality in Pediatric Body CT

    PubMed Central

    Dillman, Jonathan R.; Goodsitt, Mitchell M.; Christodoulou, Emmanuel G.; Keshavarzi, Nahid; Strouse, Peter J.

    2014-01-01

    Purpose To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection. Materials and Methods Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDIvol) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis. Results In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDIvol was 46% (range, 19%–65%) and mean decrease in SSDE was 44% (range, 19%–64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P < .002), lungs (P < .001), and bones (P < .001). By using the same reduced-dose acquisition, lesion detectability was better (38% [32 of 84 rated lesions]) or the same (62% [52 of 84 rated lesions]) with MBIR as compared with 100% ASIR. Conclusion CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality. © RSNA, 2013 Online supplemental

  7. Image reconstruction and image quality evaluation for a dual source CT scanner

    PubMed Central

    Flohr, T. G.; Bruder, H.; Stierstorfer, K.; Petersilka, M.; Schmidt, B.; McCollough, C. H.

    2008-01-01

    The authors present and evaluate concepts for image reconstruction in dual source CT (DSCT). They describe both standard spiral (helical) DSCT image reconstruction and electrocardiogram (ECG)-synchronized image reconstruction. For a compact mechanical design of the DSCT, one detector (A) can cover the full scan field of view, while the other detector (B) has to be restricted to a smaller, central field of view. The authors develop an algorithm for scan data completion, extrapolating truncated data of detector (B) by using data of detector (A). They propose a unified framework for convolution and simultaneous 3D backprojection of both (A) and (B) data, with similar treatment of standard spiral, ECG-gated spiral, and sequential (axial) scan data. In ECG-synchronized image reconstruction, a flexible scan data range per measurement system can be used to trade off temporal resolution for reduced image noise. Both data extrapolation and image reconstruction are evaluated by means of computer simulated data of anthropomorphic phantoms, by phantom measurements and patient studies. The authors show that a consistent filter direction along the spiral tangent on both detectors is essential to reduce cone-beam artifacts, requiring truncation of the extrapolated (B) data after convolution in standard spiral scans. Reconstructions of an anthropomorphic thorax phantom demonstrate good image quality and dose accumulation as theoretically expected for simultaneous 3D backprojection of the filtered (A) data and the truncated filtered (B) data into the same 3D image volume. In ECG-gated spiral modes, spiral slice sensitivity profiles (SSPs) show only minor dependence on the patient’s heart rate if the spiral pitch is properly adapted. Measurements with a thin gold plate phantom result in effective slice widths (full width at half maximum of the SSP) of 0.63–0.69mm for the nominal 0.6mm slice and 0.82–0.87mm for the nominal 0.75mm slice. The visually determined through-plane (z

  8. Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

    SciTech Connect

    Dong, Xue; Niu, Tianye; Zhu, Lei

    2014-05-15

    Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical properties of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one

  9. A technique for on-board CT reconstruction using both kilovoltage and megavoltage beam projections for 3D treatment verification.

    PubMed

    Yin, Fang-Fang; Guan, Huaiqun; Lu, Wenkai

    2005-09-01

    The technologies with kilovoltage (kV) and megavoltage (MV) imaging in the treatment room are now available for image-guided radiation therapy to improve patient setup and target localization accuracy. However, development of strategies to efficiently and effectively implement these technologies for patient treatment remains challenging. This study proposed an aggregated technique for on-board CT reconstruction using combination of kV and MV beam projections to improve the data acquisition efficiency and image quality. These projections were acquired in the treatment room at the patient treatment position with a new kV imaging device installed on the accelerator gantry, orthogonal to the existing MV portal imaging device. The projection images for a head phantom and a contrast phantom were acquired using both the On-Board Imager kV imaging device and the MV portal imager mounted orthogonally on the gantry of a Varian Clinac 21EX linear accelerator. MV projections were converted into kV information prior to the aggregated CT reconstruction. The multilevel scheme algebraic-reconstruction technique was used to reconstruct CT images involving either full, truncated, or a combination of both full and truncated projections. An adaptive reconstruction method was also applied, based on the limited numbers of kV projections and truncated MV projections, to enhance the anatomical information around the treatment volume and to minimize the radiation dose. The effects of the total number of projections, the combination of kV and MV projections, and the beam truncation of MV projections on the details of reconstructed kV/MV CT images were also investigated.

  10. Cardiac motion correction based on partial angle reconstructed images in x-ray CT

    SciTech Connect

    Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom

    2015-05-15

    Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of

  11. SU-E-I-45: Reconstruction of CT Images From Sparsely-Sampled Data Using the Logarithmic Barrier Method

    SciTech Connect

    Xu, H

    2014-06-01

    Purpose: To develop and investigate whether the logarithmic barrier (LB) method can result in high-quality reconstructed CT images using sparsely-sampled noisy projection data Methods: The objective function is typically formulated as the sum of the total variation (TV) and a data fidelity (DF) term with a parameter λ that governs the relative weight between them. Finding the optimized value of λ is a critical step for this approach to give satisfactory results. The proposed LB method avoid using λ by constructing the objective function as the sum of the TV and a log function whose augment is the DF term. Newton's method was used to solve the optimization problem. The algorithm was coded in MatLab2013b. Both Shepp-Logan phantom and a patient lung CT image were used for demonstration of the algorithm. Measured data were simulated by calculating the projection data using radon transform. A Poisson noise model was used to account for the simulated detector noise. The iteration stopped when the difference of the current TV and the previous one was less than 1%. Results: Shepp-Logan phantom reconstruction study shows that filtered back-projection (FBP) gives high streak artifacts for 30 and 40 projections. Although visually the streak artifacts are less pronounced for 64 and 90 projections in FBP, the 1D pixel profiles indicate that FBP gives noisier reconstructed pixel values than LB does. A lung image reconstruction is presented. It shows that use of 64 projections gives satisfactory reconstructed image quality with regard to noise suppression and sharp edge preservation. Conclusion: This study demonstrates that the logarithmic barrier method can be used to reconstruct CT images from sparsely-amped data. The number of projections around 64 gives a balance between the over-smoothing of the sharp demarcation and noise suppression. Future study may extend to CBCT reconstruction and improvement on computation speed.

  12. Performance evaluation of iterative reconstruction algorithms for achieving CT radiation dose reduction - a phantom study.

    PubMed

    Dodge, Cristina T; Tamm, Eric P; Cody, Dianna D; Liu, Xinming; Jensen, Corey T; Wei, Wei; Kundra, Vikas; Rong, X John

    2016-03-08

    The purpose of this study was to characterize image quality and dose performance with GE CT iterative reconstruction techniques, adaptive statistical iterative recontruction (ASiR), and model-based iterative reconstruction (MBIR), over a range of typical to low-dose intervals using the Catphan 600 and the anthropomorphic Kyoto Kagaku abdomen phantoms. The scope of the project was to quantitatively describe the advantages and limitations of these approaches. The Catphan 600 phantom, supplemented with a fat-equivalent oval ring, was scanned using a GE Discovery HD750 scanner at 120 kVp, 0.8 s rotation time, and pitch factors of 0.516, 0.984, and 1.375. The mA was selected for each pitch factor to achieve CTDIvol values of 24, 18, 12, 6, 3, 2, and 1 mGy. Images were reconstructed at 2.5 mm thickness with filtered back-projection (FBP); 20%, 40%, and 70% ASiR; and MBIR. The potential for dose reduction and low-contrast detectability were evaluated from noise and contrast-to-noise ratio (CNR) measurements in the CTP 404 module of the Catphan. Hounsfield units (HUs) of several materials were evaluated from the cylinder inserts in the CTP 404 module, and the modulation transfer function (MTF) was calculated from the air insert. The results were con-firmed in the anthropomorphic Kyoto Kagaku abdomen phantom at 6, 3, 2, and 1mGy. MBIR reduced noise levels five-fold and increased CNR by a factor of five compared to FBP below 6mGy CTDIvol, resulting in a substantial improvement in image quality. Compared to ASiR and FBP, HU in images reconstructed with MBIR were consistently lower, and this discrepancy was reversed by higher pitch factors in some materials. MBIR improved the conspicuity of the high-contrast spatial resolution bar pattern, and MTF quantification confirmed the superior spatial resolution performance of MBIR versus FBP and ASiR at higher dose levels. While ASiR and FBP were relatively insensitive to changes in dose and pitch, the spatial resolution for MBIR

  13. Insufficient ct data reconstruction based on directional total variation (dtv) regularized maximum likelihood expectation maximization (mlem) method

    NASA Astrophysics Data System (ADS)

    Islam, Fahima Fahmida

    Sparse tomography is an efficient technique which saves time as well as minimizes cost. However, due to few angular data it implies the image reconstruction problem as ill-posed. In the ill posed problem, even with exact data constraints, the inversion cannot be uniquely performed. Therefore, selection of suitable method to optimize the reconstruction problems plays an important role in sparse data CT. Use of regularization function is a well-known method to control the artifacts in limited angle data acquisition. In this work, we propose directional total variation regularized ordered subset (OS) type image reconstruction method for neutron limited data CT. Total variation (TV) regularization works as edge preserving regularization which not only preserves the sharp edge but also reduces many of the artifacts that are very common in limited data CT. However TV itself is not direction dependent. Therefore, TV is not very suitable for images with a dominant direction. The images with dominant direction it is important to know the total variation at certain direction. Hence, here a directional TV is used as prior term. TV regularization assumes the constraint of piecewise smoothness. As the original image is not piece wise constant image, sparsifying transform is used to convert the image in to sparse image or piecewise constant image. Along with this regularized function (D TV) the likelihood function which is adapted as objective function. To optimize this objective function a OS type algorithm is used. Generally there are two methods available to make OS method convergent. This work proposes OS type directional TV regularized likelihood reconstruction method which yields fast convergence as well as good quality image. Initial iteration starts with the filtered back projection (FBP) reconstructed image. The indication of convergence is determined by the convergence index between two successive reconstructed images. The quality of the image is assessed by showing

  14. A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods.

    PubMed

    Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

    2014-06-21

    As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

  15. Novel ultrahigh resolution data acquisition and image reconstruction for multi-detector row CT

    SciTech Connect

    Flohr, T. G.; Stierstorfer, K.; Suess, C.; Schmidt, B.; Primak, A. N.; McCollough, C. H.

    2007-05-15

    We present and evaluate a special ultrahigh resolution mode providing considerably enhanced spatial resolution both in the scan plane and in the z-axis direction for a routine medical multi-detector row computed tomography (CT) system. Data acquisition is performed by using a flying focal spot both in the scan plane and in the z-axis direction in combination with tantalum grids that are inserted in front of the multi-row detector to reduce the aperture of the detector elements both in-plane and in the z-axis direction. The dose utilization of the system for standard applications is not affected, since the grids are moved into place only when needed and are removed for standard scanning. By means of this technique, image slices with a nominal section width of 0.4 mm (measured full width at half maximum=0.45 mm) can be reconstructed in spiral mode on a CT system with a detector configuration of 32x0.6 mm. The measured 2% value of the in-plane modulation transfer function (MTF) is 20.4 lp/cm, the measured 2% value of the longitudinal (z axis) MTF is 21.5 lp/cm. In a resolution phantom with metal line pair test patterns, spatial resolution of 20 lp/cm can be demonstrated both in the scan plane and along the z axis. This corresponds to an object size of 0.25 mm that can be resolved. The new mode is intended for ultrahigh resolution bone imaging, in particular for wrists, joints, and inner ear studies, where a higher level of image noise due to the reduced aperture is an acceptable trade-off for the clinical benefit brought about by the improved spatial resolution.

  16. Comparison between Pre-log and Post-log Statistical Models in Ultra-Low-Dose CT Reconstruction.

    PubMed

    Fu, Lin; Lee, Tzu-Cheng; Kim, Soo Mee; Alessio, Adam; Kinahan, Paul; Chang, Zhiqian; Sauer, Ken; Kalra, Mannudeep; De Man, Bruno

    2016-11-09

    X-ray detectors in clinical computed tomography (CT) usually operate in current-integrating mode. Their complicated signal statistics often lead to intractable likelihood functions for practical use in model-based image reconstruction (MBIR). It is therefore desirable to design simplified statistical models without losing the essential factors. Depending on whether the CT transmission data are logarithmically transformed, pre-log and post-log models are two major categories of choices in CT MBIR. Both being approximations, it remains an open question whether one model can notably improve image quality over the other on real scanners. In this study, we develop and compare several pre-log and post-log MBIR algorithms under a unified framework. Their reconstruction accuracy based on simulation and clinical datasets are evaluated. The results show that pre-log MBIR can achieve notably better quantitative accuracy than post-log MBIR in ultra-low-dose CT, although in less extreme cases, post-log MBIR with handcrafted pre-processing remains a competitive alternative. Pre-log MBIR could play a growing role in emerging ultra-low-dose CT applications.

  17. Influence of dose reduction and iterative reconstruction on CT calcium scores: a multi-manufacturer dynamic phantom study.

    PubMed

    van der Werf, N R; Willemink, M J; Willems, T P; Greuter, M J W; Leiner, T

    2017-01-19

    To evaluate the influence of dose reduction in combination with iterative reconstruction (IR) on coronary calcium scores (CCS) in a dynamic phantom on state-of-the-art CT systems from different manufacturers. Calcified inserts in an anthropomorphic chest phantom were translated at 20 mm/s corresponding to heart rates between 60 and 75 bpm. The inserts were scanned five times with routinely used CCS protocols at reference dose and 40 and 80% dose reduction on four high-end CT systems. Filtered back projection (FBP) and increasing levels of IR were applied. Noise levels were determined. CCS, quantified as Agatston and mass scores, were compared to physical mass and scores at FBP reference dose. For the reference dose in combination with FBP, noise level variation between CT systems was less than 18%. Decreasing dose almost always resulted in increased CCS, while at increased levels of IR, CCS decreased again. The influence of IR on CCS was smaller than the influence of dose reduction. At reference dose, physical mass was underestimated 3-30%. All CT systems showed similar CCS at 40% dose reduction in combinations with specific reconstructions. For some CT systems CCS was not affected at 80% dose reduction, in combination with IR. This multivendor study showed that radiation dose reductions of 40% did not influence CCS in a dynamic phantom using state-of-the-art CT systems in combination with specific reconstruction settings. Dose reduction resulted in increased noise and consequently increased CCS, whereas increased IR resulted in decreased CCS.

  18. Dual energy CT with one full scan and a second sparse-view scan using structure preserving iterative reconstruction (SPIR).

    PubMed

    Wang, Tonghe; Zhu, Lei

    2016-09-21

    Conventional dual-energy CT (DECT) reconstruction requires two full-size projection datasets with two different energy spectra. In this study, we propose an iterative algorithm to enable a new data acquisition scheme which requires one full scan and a second sparse-view scan for potential reduction in imaging dose and engineering cost of DECT. A bilateral filter is calculated as a similarity matrix from the first full-scan CT image to quantify the similarity between any two pixels, which is assumed unchanged on a second CT image since DECT scans are performed on the same object. The second CT image from reduced projections is reconstructed by an iterative algorithm which updates the image by minimizing the total variation of the difference between the image and its filtered image by the similarity matrix under data fidelity constraint. As the redundant structural information of the two CT images is contained in the similarity matrix for CT reconstruction, we refer to the algorithm as structure preserving iterative reconstruction (SPIR). The proposed method is evaluated on both digital and physical phantoms, and is compared with the filtered-backprojection (FBP) method, the conventional total-variation-regularization-based algorithm (TVR) and prior-image-constrained-compressed-sensing (PICCS). SPIR with a second 10-view scan reduces the image noise STD by a factor of one order of magnitude with same spatial resolution as full-view FBP image. SPIR substantially improves over TVR on the reconstruction accuracy of a 10-view scan by decreasing the reconstruction error from 6.18% to 1.33%, and outperforms TVR at 50 and 20-view scans on spatial resolution with a higher frequency at the modulation transfer function value of 10% by an average factor of 4. Compared with the 20-view scan PICCS result, the SPIR image has 7 times lower noise STD with similar spatial resolution. The electron density map obtained from the SPIR-based DECT images with a second 10-view scan has an

  19. Dual energy CT with one full scan and a second sparse-view scan using structure preserving iterative reconstruction (SPIR)

    NASA Astrophysics Data System (ADS)

    Wang, Tonghe; Zhu, Lei

    2016-09-01

    Conventional dual-energy CT (DECT) reconstruction requires two full-size projection datasets with two different energy spectra. In this study, we propose an iterative algorithm to enable a new data acquisition scheme which requires one full scan and a second sparse-view scan for potential reduction in imaging dose and engineering cost of DECT. A bilateral filter is calculated as a similarity matrix from the first full-scan CT image to quantify the similarity between any two pixels, which is assumed unchanged on a second CT image since DECT scans are performed on the same object. The second CT image from reduced projections is reconstructed by an iterative algorithm which updates the image by minimizing the total variation of the difference between the image and its filtered image by the similarity matrix under data fidelity constraint. As the redundant structural information of the two CT images is contained in the similarity matrix for CT reconstruction, we refer to the algorithm as structure preserving iterative reconstruction (SPIR). The proposed method is evaluated on both digital and physical phantoms, and is compared with the filtered-backprojection (FBP) method, the conventional total-variation-regularization-based algorithm (TVR) and prior-image-constrained-compressed-sensing (PICCS). SPIR with a second 10-view scan reduces the image noise STD by a factor of one order of magnitude with same spatial resolution as full-view FBP image. SPIR substantially improves over TVR on the reconstruction accuracy of a 10-view scan by decreasing the reconstruction error from 6.18% to 1.33%, and outperforms TVR at 50 and 20-view scans on spatial resolution with a higher frequency at the modulation transfer function value of 10% by an average factor of 4. Compared with the 20-view scan PICCS result, the SPIR image has 7 times lower noise STD with similar spatial resolution. The electron density map obtained from the SPIR-based DECT images with a second 10-view scan has an

  20. A CT reconstruction approach from sparse projection with adaptive-weighted diagonal total-variation in biomedical application.

    PubMed

    Deng, Luzhen; Mi, Deling; He, Peng; Feng, Peng; Yu, Pengwei; Chen, Mianyi; Li, Zhichao; Wang, Jian; Wei, Biao

    2015-01-01

    For lack of directivity in Total Variation (TV) which only uses x-coordinate and y-coordinate gradient transform as its sparse representation approach during the iteration process, this paper brought in Adaptive-weighted Diagonal Total Variation (AwDTV) that uses the diagonal direction gradient to constraint reconstructed image and adds associated weights which are expressed as an exponential function and can be adaptively adjusted by the local image-intensity diagonal gradient for the purpose of preserving the edge details, then using the steepest descent method to solve the optimization problem. Finally, we did two sets of numerical simulation and the results show that the proposed algorithm can reconstruct high-quality CT images from few-views projection, which has lower Root Mean Square Error (RMSE) and higher Universal Quality Index (UQI) than Algebraic Reconstruction Technique (ART) and TV-based reconstruction method.

  1. Noise suppression in reconstruction of low-Z target megavoltage cone-beam CT images

    SciTech Connect

    Wang Jing; Robar, James; Guan Huaiqun

    2012-08-15

    Purpose: To improve the image contrast-to-noise (CNR) ratio for low-Z target megavoltage cone-beam CT (MV CBCT) using a statistical projection noise suppression algorithm based on the penalized weighted least-squares (PWLS) criterion. Methods: Projection images of a contrast phantom, a CatPhan{sup Registered-Sign} 600 phantom and a head phantom were acquired by a Varian 2100EX LINAC with a low-Z (Al) target and low energy x-ray beam (2.5 MeV) at a low-dose level and at a high-dose level. The projections were then processed by minimizing the PWLS objective function. The weighted least square (WLS) term models the noise of measured projection and the penalty term enforces the smoothing constraints of the projection image. The variance of projection data was chosen as the weight for the PWLS objective function and it determined the contribution of each measurement. An anisotropic quadratic form penalty that incorporates the gradient information of projection image was used to preserve edges during noise reduction. Low-Z target MV CBCT images were reconstructed by the FDK algorithm after each projection was processed by the PWLS smoothing. Results: Noise in low-Z target MV CBCT images were greatly suppressed after the PWLS projection smoothing, without noticeable sacrifice of the spatial resolution. Depending on the choice of smoothing parameter, the CNR of selected regions of interest in the PWLS processed low-dose low-Z target MV CBCT image can be higher than the corresponding high-dose image.Conclusion: The CNR of low-Z target MV CBCT images was substantially improved by using PWLS projection smoothing. The PWLS projection smoothing algorithm allows the reconstruction of high contrast low-Z target MV CBCT image with a total dose of as low as 2.3 cGy.

  2. Optimization of image reconstruction for yttrium-90 SIRT on a LYSO PET/CT system using a Bayesian penalized likelihood reconstruction algorithm.

    PubMed

    Rowley, Lisa M; Bradley, Kevin M; Boardman, Philip; Hallam, Aida; McGowan, Daniel R

    2016-09-29

    Imaging on a gamma camera with Yttrium-90 ((90)Y) following selective internal radiotherapy (SIRT) may allow for verification of treatment delivery but suffers relatively poor spatial resolution and imprecise dosimetry calculation. (90)Y Positron Emission Tomography (PET) / Computed Tomography (CT) imaging is possible on 3D, time-of-flight machines however images are usually poor due to low count statistics and noise. A new PET reconstruction software using a Bayesian penalized likelihood (BPL) reconstruction algorithm (termed Q.Clear) released by GE was investigated using phantom and patient scans to optimize the reconstruction for post-SIRT imaging and clarify if this leads to an improvement in clinical image quality using (90)Y.

  3. SU-D-12A-05: Iterative Reconstruction Techniques to Enable Intrinsic Respiratory Gated CT in Mice

    SciTech Connect

    Sun, T; Sun, N; Tan, S; Liu, Y; Mistry, N

    2014-06-01

    Purpose: Longitudinal studies of lung function in mice need the ability to image different phases of ventilation in free-breathing mice using retrospective gating. However, retrospective gating often produces under-sampled and uneven angular samples, resulting in severe reconstruction artifacts when using traditional FDK based reconstruction algorithms. We wanted to demonstrate the utility of iterative reconstruction method to enable intrinsic respiratory gating in small-animal CT. Methods: Free-breathing mice were imaged using a Siemens Inveon PET/micro-CT system. Evenly distributed projection images were acquired at 360 angles. Retrospective respiratory gating was performed using an intrinsic marker based on the average intensity in a region covering the diaphragm. Projections were classified into 4 and 6 phases (finer temporal resolution) resulting in 138 and 67 projections respectively. Reconstruction was carried out using 3 Methods: conventional FDK, iterative penalized least-square (PWLS) with total variation (TV), and PWLS with edge-preserving penalty. The performance of the methods was compared using contrast-to-noise (CNR) in a region of interest (ROI). Line profile through a specific region was plotted to evaluate the preserving of edges. Results: In both the cases with 4 and 6 phases, inadequate and non-uniform angular sampling results in artifacts using conventional FDK. However, such artifacts are minimized using both the iterative methods. Using both 4 and 6 phases, the iterative techniques outperformed FDK in terms of CNR and maintaining sharp edges. This is further evidenced especially with increased artifacts using FDK for 6 phases. Conclusion: This work indicates fewer artifacts and better image details can be achieved with iterative reconstruction methods in non-uniform under-sampled reconstruction. Using iterative methods can enable free-breathing intrinsic respiratory gating in small-animal CT. Further studies are needed to compare the

  4. DQS advisor: a visual interface and knowledge-based system to balance dose, quality, and reconstruction speed in iterative CT reconstruction with application to NLM-regularization.

    PubMed

    Zheng, Z; Papenhausen, E; Mueller, K

    2013-11-07

    Motivated by growing concerns with regards to the x-ray dose delivered to the patient, low-dose computed tomography (CT) has gained substantial interest in recent years. However, achieving high-quality CT reconstructions from the limited projection data collected at reduced x-ray radiation is challenging, and iterative algorithms have been shown to perform much better than conventional analytical schemes in these cases. A problem with iterative methods in general is that they require users to set many parameters, and if set incorrectly high reconstruction time and/or low image quality are likely consequences. Since the interactions among parameters can be complex and thus effective settings can be difficult to identify for a given scanning scenario, these choices are often left to a highly-experienced human expert. To help alleviate this problem, we devise a computer-based assistant for this purpose, called dose, quality and speed (DQS)-advisor. It allows users to balance the three most important CT metrics--DQS--by ways of an intuitive visual interface. Using a known gold-standard, the system uses the ant-colony optimization algorithm to generate the most effective parameter settings for a comprehensive set of DQS configurations. A visual interface then presents the numerical outcome of this optimization, while a matrix display allows users to compare the corresponding images. The interface allows users to intuitively trade-off GPU-enabled reconstruction speed with quality and dose, while the system picks the associated parameter settings automatically. Further, once the knowledge has been generated, it can be used to correctly set the parameters for any new CT scan taken at similar scenarios.

  5. Dose reduction with iterative reconstruction for coronary CT angiography: a systematic review and meta-analysis

    PubMed Central

    Willemink, Martin J; De Ruiter, Quirina M B; De Jong, Pim A; Schilham, Arnold M R; Krestin, Gabriel P; Leiner, Tim; Budde, Ricardo P J

    2016-01-01

    Objective: To investigate the achievable radiation dose reduction for coronary CT angiography (CCTA) with iterative reconstruction (IR) in adults and the effects on image quality. Methods: PubMed and EMBASE were searched, and original articles concerning IR for CCTA in adults using prospective electrocardiogram triggering were included. Primary outcome was the effective dose using filtered back projection (FBP) and IR. Secondary outcome was the effect of IR on objective and subjective image quality. Results: The search yielded 1616 unique articles, of which 10 studies (1042 patients) were included. The pooled routine effective dose with FBP was 4.2 mSv [95% confidence interval (CI) 3.5–5.0]. A dose reduction of 48% to a pooled effective dose of 2.2 mSv (95% CI 1.3–3.1) using IR was reported. Noise, contrast-to-noise ratio and subjective image quality were equal or improved in all but one study, whereas signal-to-noise ratio was decreased in two studies with IR at reduced dose. Conclusion: IR allows for CCTA acquisition with an effective dose of 2.2 mSv with preserved objective and subjective image quality. PMID:26562096

  6. Three-dimensional model of the skull and the cranial bones reconstructed from CT scans designed for rapid prototyping process.

    PubMed

    Skrzat, Janusz; Spulber, Alexandru; Walocha, Jerzy

    2016-01-01

    This paper presents the effects of building mesh models of the human skull and the cranial bones from a series of CT-scans. With the aid of computer so ware, 3D reconstructions of the whole skull and segmented cranial bones were performed and visualized by surface rendering techniques. The article briefly discusses clinical and educational applications of 3D cranial models created using stereolitographic reproduction.

  7. Ultralow dose dentomaxillofacial CT imaging and iterative reconstruction techniques: variability of Hounsfield units and contrast-to-noise ratio

    PubMed Central

    Bischel, Alexander; Stratis, Andreas; Kakar, Apoorv; Bosmans, Hilde; Jacobs, Reinhilde; Gassner, Eva-Maria; Puelacher, Wolfgang; Pauwels, Ruben

    2016-01-01

    Objective: The aim of this study was to evaluate whether application of ultralow dose protocols and iterative reconstruction technology (IRT) influence quantitative Hounsfield units (HUs) and contrast-to-noise ratio (CNR) in dentomaxillofacial CT imaging. Methods: A phantom with inserts of five types of materials was scanned using protocols for (a) a clinical reference for navigated surgery (CT dose index volume 36.58 mGy), (b) low-dose sinus imaging (18.28 mGy) and (c) four ultralow dose imaging (4.14, 2.63, 0.99 and 0.53 mGy). All images were reconstructed using: (i) filtered back projection (FBP); (ii) IRT: adaptive statistical iterative reconstruction-50 (ASIR-50), ASIR-100 and model-based iterative reconstruction (MBIR); and (iii) standard (std) and bone kernel. Mean HU, CNR and average HU error after recalibration were determined. Each combination of protocols was compared using Friedman analysis of variance, followed by Dunn's multiple comparison test. Results: Pearson's sample correlation coefficients were all >0.99. Ultralow dose protocols using FBP showed errors of up to 273 HU. Std kernels had less HU variability than bone kernels. MBIR reduced the error value for the lowest dose protocol to 138 HU and retained the highest relative CNR. ASIR could not demonstrate significant advantages over FBP. Conclusions: Considering a potential dose reduction as low as 1.5% of a std protocol, ultralow dose protocols and IRT should be further tested for clinical dentomaxillofacial CT imaging. Advances in knowledge: HU as a surrogate for bone density may vary significantly in CT ultralow dose imaging. However, use of std kernels and MBIR technology reduce HU error values and may retain the highest CNR. PMID:26859336

  8. Regularized ML reconstruction for time/dose reduction in 18F-fluoride PET/CT studies

    NASA Astrophysics Data System (ADS)

    De Bernardi, Elisabetta; Magnani, Patrizia; Gianolli, Luigi; Carla Gilardi, Maria; Bettinardi, Valentino

    2015-01-01

    We are proposing a regularized reconstruction strategy for the detection of bone lesions in 18F-fluoride whole body PET images obtained with 1 min/bed using the anatomical information provided by co-registered CT images. Bones are recognized on CT images and then transposed into the PET volume framework. During PET reconstruction, two different priors are used for bone and non-bone voxels: the relative difference prior in bone and the P-Gaussian prior in non-bone. After a tuning of the priors’ parameters, the reconstruction strategy has been tested on 6 18F-fluoride PET/CT studies, on a total of 67 lesions. Regularized images provided results comparable to the standard 3 min/bed images, in terms image quality, lesion activity, noise level and noise correlation. The proposed strategy therefore appears to be a useful tool to reduce the acquisition time or the injected dose in 18F-fluoride PET studies.

  9. Study of the radiation dose reduction capability of a CT reconstruction algorithm: LCD performance assessment using mathematical model observers

    NASA Astrophysics Data System (ADS)

    Fan, Jiahua; Tseng, Hsin-Wu; Kupinski, Matthew; Cao, Guangzhi; Sainath, Paavana; Hsieh, Jiang

    2013-03-01

    Radiation dose on patient has become a major concern today for Computed Tomography (CT) imaging in clinical practice. Various hardware and algorithm solutions have been designed to reduce dose. Among them, iterative reconstruction (IR) has been widely expected to be an effective dose reduction approach for CT. However, there is no clear understanding on the exact amount of dose saving an IR approach can offer for various clinical applications. We know that quantitative image quality assessment should be task-based. This work applied mathematical model observers to study detectability performance of CT scan data reconstructed using an advanced IR approach as well as the conventional filtered back-projection (FBP) approach. The purpose of this work is to establish a practical and robust approach for CT IR detectability image quality evaluation and to assess the dose saving capability of the IR method under study. Low contrast (LC) objects imbedded in head size and body size phantoms were imaged multiple times with different dose levels. Independent signal present and absent pairs were generated for model observer study training and testing. Receiver Operating Characteristic (ROC) curves for location known exact and location ROC (LROC) curves for location unknown as well as their corresponding the area under the curve (AUC) values were calculated. Results showed approximately 3 times dose reduction has been achieved using the IR method under study.

  10. Effects of voxel size and iterative reconstruction parameters on the spatial resolution of 99mTc SPECT/CT.

    PubMed

    Kappadath, S Cheenu

    2011-11-15

    The purpose of this study was to evaluate the effects of voxel size and iterative reconstruction parameters on the radial and tangential resolution for 99mTc SPECT as a function of radial distance from isocenter. SPECT/CT scans of eight coplanar point sources of size smaller than 1 mm3 containing high concentration 99mTc solution were acquired on a SPECT/CT system with 5/8 inch NaI(Tl) detector and low-energy, high-resolution collimator. The tomographic projection images were acquired in step-and-shoot mode for 360 views over 360° with 250,000 counts per view, a zoom of 2.67, and an image matrix of 256 × 256 pixels that resulted in a 0.9 × 0.9 × 0.9 mm3 SPECT voxel size over 230 mm field-of-view. The projection images were also rebinned to image matrices of 128 × 128 and 64 × 64 to yield SPECT voxel sizes of 1.8 × 1.8 × 1.8 and 3.6 × 3.6 × 3.6 mm3, respectively. The SPECT/CT datasets were reconstructed using the vendor-supplied iterative reconstruction software that incorporated collimator-specific resolution recovery, CT-based attenuation correction, and dual-energy window-based scatter correction using different combinations of iterations and subsets. SPECT spatial resolution was estimated as the full width at half maximum of the radial and tangential profiles through the center of each point source in reconstructed SPECT images. Both radial and tangential resolution improved with higher iterations and subsets, and with smaller voxel sizes. Both radial and tangential resolution also improved with radial distance further away from isocenter. The magnitude of variation decreased for smaller voxel sizes and for higher number of iterations and subsets. Tangential resolution was found not to be equal to the radial resolution, and the nature of the anisotropy depended on the distribution of the radionuclide and on the reconstruction parameters used. The tangential resolution converged faster than the radial resolution, with higher iterations and subsets

  11. A comparative study based on image quality and clinical task performance for CT reconstruction algorithms in radiotherapy.

    PubMed

    Li, Hua; Dolly, Steven; Chen, Hsin-Chen; Anastasio, Mark A; Low, Daniel A; Li, Harold H; Michalski, Jeff M; Thorstad, Wade L; Gay, Hiram; Mutic, Sasa

    2016-07-01

    CT image reconstruction is typically evaluated based on the ability to reduce the radiation dose to as-low-as-reasonably-achievable (ALARA) while maintaining acceptable image quality. However, the determination of common image quality metrics, such as noise, contrast, and contrast-to-noise ratio, is often insufficient for describing clinical radiotherapy task performance. In this study we designed and implemented a new comparative analysis method associating image quality, radiation dose, and patient size with radiotherapy task performance, with the purpose of guiding the clinical radiotherapy usage of CT reconstruction algorithms. The iDose4iterative reconstruction algorithm was selected as the target for comparison, wherein filtered back-projection (FBP) reconstruction was regarded as the baseline. Both phantom and patient images were analyzed. A layer-adjustable anthropomorphic pelvis phantom capable of mimicking 38-58 cm lateral diameter-sized patients was imaged and reconstructed by the FBP and iDose4 algorithms with varying noise-reduction-levels, respectively. The resulting image sets were quantitatively assessed by two image quality indices, noise and contrast-to-noise ratio, and two clinical task-based indices, target CT Hounsfield number (for electron density determination) and structure contouring accuracy (for dose-volume calculations). Additionally, CT images of 34 patients reconstructed with iDose4 with six noise reduction levels were qualitatively evaluated by two radiation oncologists using a five-point scoring mechanism. For the phantom experiments, iDose4 achieved noise reduction up to 66.1% and CNR improvement up to 53.2%, compared to FBP without considering the changes of spatial resolution among images and the clinical acceptance of reconstructed images. Such improvements consistently appeared across different iDose4 noise reduction levels, exhibiting limited interlevel noise (<5 HU) and target CT number variations (<1 HU). The radiation

  12. A comparative study based on image quality and clinical task performance for CT reconstruction algorithms in radiotherapy.

    PubMed

    Li, Hua; Dolly, Steven; Chen, Hsin-Chen; Anastasio, Mark A; Low, Daniel A; Li, Harold H; Michalski, Jeff M; Thorstad, Wade L; Gay, Hiram; Mutic, Sasa

    2016-07-08

    CT image reconstruction is typically evaluated based on the ability to reduce the radiation dose to as-low-as-reasonably-achievable (ALARA) while maintaining acceptable image quality. However, the determination of common image quality metrics, such as noise, contrast, and contrast-to-noise ratio, is often insufficient for describing clinical radiotherapy task performance. In this study we designed and implemented a new comparative analysis method associating image quality, radiation dose, and patient size with radiotherapy task performance, with the purpose of guiding the clinical radiotherapy usage of CT reconstruction algorithms. The iDose4 iterative reconstruction algorithm was selected as the target for comparison, wherein filtered back-projection (FBP) reconstruction was regarded as the baseline. Both phantom and patient images were analyzed. A layer-adjustable anthropomorphic pelvis phantom capable of mimicking 38-58 cm lateral diameter-sized patients was imaged and reconstructed by the FBP and iDose4 algorithms with varying noise-reduction-levels, respectively. The resulting image sets were quantitatively assessed by two image quality indices, noise and contrast-to-noise ratio, and two clinical task-based indices, target CT Hounsfield number (for electron density determination) and structure contouring accuracy (for dose-volume calculations). Additionally, CT images of 34 patients reconstructed with iDose4 with six noise reduction levels were qualitatively evaluated by two radiation oncologists using a five-point scoring mechanism. For the phantom experiments, iDose4 achieved noise reduction up to 66.1% and CNR improvement up to 53.2%, compared to FBP without considering the changes of spatial resolution among images and the clinical acceptance of reconstructed images. Such improvements consistently appeared across different iDose4 noise reduction levels, exhibiting limited interlevel noise (< 5 HU) and target CT number variations (< 1 HU). The radiation

  13. Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

    PubMed Central

    Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

    2016-01-01

    Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications. PMID:27181695

  14. Efficient and robust 3D CT image reconstruction based on total generalized variation regularization using the alternating direction method.

    PubMed

    Chen, Jianlin; Wang, Linyuan; Yan, Bin; Zhang, Hanming; Cheng, Genyang

    2015-01-01

    Iterative reconstruction algorithms for computed tomography (CT) through total variation regularization based on piecewise constant assumption can produce accurate, robust, and stable results. Nonetheless, this approach is often subject to staircase artefacts and the loss of fine details. To overcome these shortcomings, we introduce a family of novel image regularization penalties called total generalized variation (TGV) for the effective production of high-quality images from incomplete or noisy projection data for 3D reconstruction. We propose a new, fast alternating direction minimization algorithm to solve CT image reconstruction problems through TGV regularization. Based on the theory of sparse-view image reconstruction and the framework of augmented Lagrange function method, the TGV regularization term has been introduced in the computed tomography and is transformed into three independent variables of the optimization problem by introducing auxiliary variables. This new algorithm applies a local linearization and proximity technique to make the FFT-based calculation of the analytical solutions in the frequency domain feasible, thereby significantly reducing the complexity of the algorithm. Experiments with various 3D datasets corresponding to incomplete projection data demonstrate the advantage of our proposed algorithm in terms of preserving fine details and overcoming the staircase effect. The computation cost also suggests that the proposed algorithm is applicable to and is effective for CBCT imaging. Theoretical and technical optimization should be investigated carefully in terms of both computation efficiency and high resolution of this algorithm in application-oriented research.

  15. Investigation on viewing direction dependent detectability in a reconstructed 3D volume for a cone beam CT system

    NASA Astrophysics Data System (ADS)

    Park, Junhan; Lee, Changwoo; Baek, Jongduk

    2015-03-01

    In medical imaging systems, several factors (e.g., reconstruction algorithm, noise structures, target size, contrast, etc) affect the detection performance and need to be considered for object detection. In a cone beam CT system, FDK reconstruction produces different noise structures in axial and coronal slices, and thus we analyzed directional dependent detectability of objects using detection SNR of Channelized Hotelling observer. To calculate the detection SNR, difference-of-Gaussian channel model with 10 channels was implemented, and 20 sphere objects with different radius (i.e., 0.25 (mm) to 5 (mm) equally spaced by 0.25 (mm)), reconstructed by FDK algorithm, were used as object templates. Covariance matrix in axial and coronal direction was estimated from 3000 reconstructed noise volumes, and then the SNR ratio between axial and coronal direction was calculated. Corresponding 2D noise power spectrum was also calculated. The results show that as the object size increases, the SNR ratio decreases, especially lower than 1 when the object size is larger than 2.5 mm radius. The reason is because the axial (coronal) noise power is higher in high (low) frequency band, and therefore the detectability of a small (large) object is higher in coronal (axial) images. Our results indicate that it is more beneficial to use coronal slices in order to improve the detectability of a small object in a cone beam CT system.

  16. The effect of CT dose on glenohumeral joint congruency measurements using 3D reconstructed patient-specific bone models

    NASA Astrophysics Data System (ADS)

    Lalone, Emily A.; Fox, Anne-Marie V.; Kedgley, Angela E.; Jenkyn, Thomas R.; King, Graham J. W.; Athwal, George S.; Johnson, James A.; Peters, Terry M.

    2011-10-01

    The study of joint congruency at the glenohumeral joint of the shoulder using computed tomography (CT) and three-dimensional (3D) reconstructions of joint surfaces is an area of significant clinical interest. However, ionizing radiation delivered to patients during CT examinations is much higher than other types of radiological imaging. The shoulder represents a significant challenge for this modality as it is adjacent to the thyroid gland and breast tissue. The objective of this study was to determine the optimal CT scanning techniques that would minimize radiation dose while accurately quantifying joint congruency of the shoulder. The results suggest that only one-tenth of the standard applied total current (mA) and a pitch ratio of 1.375:1 was necessary to produce joint congruency values consistent with that of the higher dose scans. Using the CT scanning techniques examined in this study, the effective dose applied to the shoulder to quantify joint congruency was reduced by 88.9% compared to standard clinical CT imaging techniques.

  17. Full dose reduction potential of statistical iterative reconstruction for head CT protocols in a predominantly pediatric population

    PubMed Central

    Mirro, Amy E.; Brady, Samuel L.; Kaufman, Robert. A.

    2016-01-01

    Purpose To implement the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population. Methods Select head examinations (brain, orbits, sinus, maxilla and temporal bones) were investigated. Dose-reduced head protocols using an adaptive statistical iterative reconstruction (ASiR) were compared for image quality with the original filtered back projection (FBP) reconstructed protocols in phantom using the following metrics: image noise frequency (change in perceived appearance of noise texture), image noise magnitude, contrast-to-noise ratio (CNR), and spatial resolution. Dose reduction estimates were based on computed tomography dose index (CTDIvol) values. Patient CTDIvol and image noise magnitude were assessed in 737 pre and post dose reduced examinations. Results Image noise texture was acceptable up to 60% ASiR for Soft reconstruction kernel (at both 100 and 120 kVp), and up to 40% ASiR for Standard reconstruction kernel. Implementation of 40% and 60% ASiR led to an average reduction in CTDIvol of 43% for brain, 41% for orbits, 30% maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years, while maintaining an average noise magnitude difference of 0.1% (range: −3% to 5%), improving CNR of low contrast soft tissue targets, and improving spatial resolution of high contrast bony anatomy, as compared to FBP. Conclusion The methodology in this study demonstrates a methodology for maximizing patient dose reduction and maintaining image quality using statistical iterative reconstruction for a primarily pediatric population undergoing head CT examination. PMID:27056425

  18. Noise properties of CT images reconstructed by use of constrained total-variation, data-discrepancy minimization

    PubMed Central

    Rose, Sean; Andersen, Martin S.; Sidky, Emil Y.; Pan, Xiaochuan

    2015-01-01

    Purpose: The authors develop and investigate iterative image reconstruction algorithms based on data-discrepancy minimization with a total-variation (TV) constraint. The various algorithms are derived with different data-discrepancy measures reflecting the maximum likelihood (ML) principle. Simulations demonstrate the iterative algorithms and the resulting image statistical properties for low-dose CT data acquired with sparse projection view angle sampling. Of particular interest is to quantify improvement of image statistical properties by use of the ML data fidelity term. Methods: An incremental algorithm framework is developed for this purpose. The instances of the incremental algorithms are derived for solving optimization problems including a data fidelity objective function combined with a constraint on the image TV. For the data fidelity term the authors, compare application of the maximum likelihood principle, in the form of weighted least-squares (WLSQ) and Poisson-likelihood (PL), with the use of unweighted least-squares (LSQ). Results: The incremental algorithms are applied to projection data generated by a simulation modeling the breast computed tomography (bCT) imaging application. The only source of data inconsistency in the bCT projections is due to noise, and a Poisson distribution is assumed for the transmitted x-ray photon intensity. In the simulations involving the incremental algorithms an ensemble of images, reconstructed from 1000 noise realizations of the x-ray transmission data, is used to estimate the image statistical properties. The WLSQ and PL incremental algorithms are seen to reduce image variance as compared to that of LSQ without sacrificing image bias. The difference is also seen at few iterations—short of numerical convergence of the corresponding optimization problems. Conclusions: The proposed incremental algorithms prove effective and efficient for iterative image reconstruction in low-dose CT applications particularly with

  19. SU-E-J-153: Reconstructing 4D Cone Beam CT Images for Clinical QA of Lung SABR Treatments

    SciTech Connect

    Beaudry, J; Bergman, A; Cropp, R

    2015-06-15

    Purpose: To verify that the planned Primary Target Volume (PTV) and Internal Gross Tumor Volume (IGTV) fully enclose a moving lung tumor volume as visualized on a pre-SABR treatment verification 4D Cone Beam CT. Methods: Daily 3DCBCT image sets were acquired immediately prior to treatment for 10 SABR lung patients using the on-board imaging system integrated into a Varian TrueBeam (v1.6: no 4DCBCT module available). Respiratory information was acquired during the scan using the Varian RPM system. The CBCT projections were sorted into 8 bins offline, both by breathing phase and amplitude, using in-house software. An iterative algorithm based on total variation minimization, implemented in the open source reconstruction toolkit (RTK), was used to reconstruct the binned projections into 4DCBCT images. The relative tumor motion was quantified by tracking the centroid of the tumor volume from each 4DCBCT image. Following CT-CBCT registration, the planning CT volumes were compared to the location of the CBCT tumor volume as it moves along its breathing trajectory. An overlap metric quantified the ability of the planned PTV and IGTV to contain the tumor volume at treatment. Results: The 4DCBCT reconstructed images visibly show the tumor motion. The mean overlap between the planned PTV (IGTV) and the 4DCBCT tumor volumes was 100% (94%), with an uncertainty of 5% from the 4DCBCT tumor volume contours. Examination of the tumor motion and overlap metric verify that the IGTV drawn at the planning stage is a good representation of the tumor location at treatment. Conclusion: It is difficult to compare GTV volumes from a 4DCBCT and a planning CT due to image quality differences. However, it was possible to conclude the GTV remained within the PTV 100% of the time thus giving the treatment staff confidence that SABR lung treatements are being delivered accurately.

  20. Preliminary study of region-of-interest image reconstruction with intensity weighting in cone-beam CT using iterative algorithm

    NASA Astrophysics Data System (ADS)

    Son, Kihong; Lee, Jiseoc; Lee, Younjeong; Kim, Jin Sung; Cho, Seungryong

    2014-03-01

    In computed tomography (CT) imaging, radiat ion dose delivered to the patient is one of the major concerns. Many CT developers and researchers have been making efforts to reduce radiat ion dose. Spars e-view CT takes project ions at sparser view-angles and provides a viable option to reducing radiation dose. Sparse-view CT inspired by a compressive sensing (CS) theory, which acquires sparsely sampled data in projection angles to reconstruct volumetric images of the scanned object, is under active research for low-dose imaging. Also, region of interest (ROI) imaging method is one of the reasonable approaches to reducing the integral dose to the patient and the risk of overdose. In this study, we combined the two approaches together to achieve an ultra-low-dose imaging: a sparse-view imaging and the intensityweighted region-of-interest (IWROI) imaging. IWROI imaging technique is particularly interesting because it can reduce the imaging radiation dose substantially to the structures away from the imaging target, while allowing a stable solution of the reconstruction problem in comparison with the interior problem. We used a total-variation (TV) minimization algorithm that exploits the sparseness of the image derivative magnitude and can reconstruct images from sparse-view data. In this study, we implemented an imaging mode that combines a sparse-view imaging and an ROI imaging. We obtained promising results and believe that the proposed scanning approach can help reduce radiation dose to the patients while preserving good quality images for applications such as image-guided radiation therapy. We are in progress of applying the method to the real data.

  1. Task-based image quality evaluation of iterative reconstruction methods for low dose CT using computer simulations

    NASA Astrophysics Data System (ADS)

    Xu, Jingyan; Fuld, Matthew K.; Fung, George S. K.; Tsui, Benjamin M. W.

    2015-04-01

    Iterative reconstruction (IR) methods for x-ray CT is a promising approach to improve image quality or reduce radiation dose to patients. The goal of this work was to use task based image quality measures and the channelized Hotelling observer (CHO) to evaluate both analytic and IR methods for clinical x-ray CT applications. We performed realistic computer simulations at five radiation dose levels, from a clinical reference low dose D0 to 25% D0. A fixed size and contrast lesion was inserted at different locations into the liver of the XCAT phantom to simulate a weak signal. The simulated data were reconstructed on a commercial CT scanner (SOMATOM Definition Flash; Siemens, Forchheim, Germany) using the vendor-provided analytic (WFBP) and IR (SAFIRE) methods. The reconstructed images were analyzed by CHOs with both rotationally symmetric (RS) and rotationally oriented (RO) channels, and with different numbers of lesion locations (5, 10, and 20) in a signal known exactly (SKE), background known exactly but variable (BKEV) detection task. The area under the receiver operating characteristic curve (AUC) was used as a summary measure to compare the IR and analytic methods; the AUC was also used as the equal performance criterion to derive the potential dose reduction factor of IR. In general, there was a good agreement in the relative AUC values of different reconstruction methods using CHOs with RS and RO channels, although the CHO with RO channels achieved higher AUCs than RS channels. The improvement of IR over analytic methods depends on the dose level. The reference dose level D0 was based on a clinical low dose protocol, lower than the standard dose due to the use of IR methods. At 75% D0, the performance improvement was statistically significant (p < 0.05). The potential dose reduction factor also depended on the detection task. For the SKE/BKEV task involving 10 lesion locations, a dose reduction of at least 25% from D0 was achieved.

  2. Six iterative reconstruction algorithms in brain CT: a phantom study on image quality at different radiation dose levels

    PubMed Central

    Olsson, M-L; Siemund, R; Stålhammar, F; Björkman-Burtscher, I M; Söderberg, M

    2013-01-01

    Objective: To evaluate the image quality produced by six different iterative reconstruction (IR) algorithms in four CT systems in the setting of brain CT, using different radiation dose levels and iterative image optimisation levels. Methods: An image quality phantom, supplied with a bone mimicking annulus, was examined using four CT systems from different vendors and four radiation dose levels. Acquisitions were reconstructed using conventional filtered back-projection (FBP), three levels of statistical IR and, when available, a model-based IR algorithm. The evaluated image quality parameters were CT numbers, uniformity, noise, noise-power spectra, low-contrast resolution and spatial resolution. Results: Compared with FBP, noise reduction was achieved by all six IR algorithms at all radiation dose levels, with further improvement seen at higher IR levels. Noise-power spectra revealed changes in noise distribution relative to the FBP for most statistical IR algorithms, especially the two model-based IR algorithms. Compared with FBP, variable degrees of improvements were seen in both objective and subjective low-contrast resolutions for all IR algorithms. Spatial resolution was improved with both model-based IR algorithms and one of the statistical IR algorithms. Conclusion: The four statistical IR algorithms evaluated in the study all improved the general image quality compared with FBP, with improvement seen for most or all evaluated quality criteria. Further improvement was achieved with one of the model-based IR algorithms. Advances in knowledge: The six evaluated IR algorithms all improve the image quality in brain CT but show different strengths and weaknesses. PMID:24049128

  3. List-mode reconstruction for the Biograph mCT with physics modeling and event-by-event motion correction

    NASA Astrophysics Data System (ADS)

    Jin, Xiao; Chan, Chung; Mulnix, Tim; Panin, Vladimir; Casey, Michael E.; Liu, Chi; Carson, Richard E.

    2013-08-01

    Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion

  4. MIRD pamphlet No. 23: quantitative SPECT for patient-specific 3-dimensional dosimetry in internal radionuclide therapy.

    PubMed

    Dewaraja, Yuni K; Frey, Eric C; Sgouros, George; Brill, A Bertrand; Roberson, Peter; Zanzonico, Pat B; Ljungberg, Michael

    2012-08-01

    In internal radionuclide therapy, a growing interest in voxel-level estimates of tissue-absorbed dose has been driven by the desire to report radiobiologic quantities that account for the biologic consequences of both spatial and temporal nonuniformities in these dose estimates. This report presents an overview of 3-dimensional SPECT methods and requirements for internal dosimetry at both regional and voxel levels. Combined SPECT/CT image-based methods are emphasized, because the CT-derived anatomic information allows one to address multiple technical factors that affect SPECT quantification while facilitating the patient-specific voxel-level dosimetry calculation itself. SPECT imaging and reconstruction techniques for quantification in radionuclide therapy are not necessarily the same as those designed to optimize diagnostic imaging quality. The current overview is intended as an introduction to an upcoming series of MIRD pamphlets with detailed radionuclide-specific recommendations intended to provide best-practice SPECT quantification-based guidance for radionuclide dosimetry.

  5. Applications of nonlocal means algorithm in low-dose X-ray CT image processing and reconstruction: A review.

    PubMed

    Zhang, Hao; Zeng, Dong; Zhang, Hua; Wang, Jing; Liang, Zhengrong; Ma, Jianhua

    2017-03-01

    Low-dose X-ray computed tomography (LDCT) imaging is highly recommended for use in the clinic because of growing concerns over excessive radiation exposure. However, the CT images reconstructed by the conventional filtered back-projection (FBP) method from low-dose acquisitions may be severely degraded with noise and streak artifacts due to excessive X-ray quantum noise, or with view-aliasing artifacts due to insufficient angular sampling. In 2005, the nonlocal means (NLM) algorithm was introduced as a non-iterative edge-preserving filter to denoise natural images corrupted by additive Gaussian noise, and showed superior performance. It has since been adapted and applied to many other image types and various inverse problems. This paper specifically reviews the applications of the NLM algorithm in LDCT image processing and reconstruction, and explicitly demonstrates its improving effects on the reconstructed CT image quality from low-dose acquisitions. The effectiveness of these applications on LDCT and their relative performance are described in detail.

  6. GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration

    NASA Astrophysics Data System (ADS)

    Sharp, G. C.; Kandasamy, N.; Singh, H.; Folkert, M.

    2007-09-01

    This paper shows how to significantly accelerate cone-beam CT reconstruction and 3D deformable image registration using the stream-processing model. We describe data-parallel designs for the Feldkamp, Davis and Kress (FDK) reconstruction algorithm, and the demons deformable registration algorithm, suitable for use on a commodity graphics processing unit. The streaming versions of these algorithms are implemented using the Brook programming environment and executed on an NVidia 8800 GPU. Performance results using CT data of a preserved swine lung indicate that the GPU-based implementations of the FDK and demons algorithms achieve a substantial speedup—up to 80 times for FDK and 70 times for demons when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementations was found to be excellent. Compared with CPU-based implementations, the RMS differences were less than 0.1 Hounsfield unit for reconstruction and less than 0.1 mm for deformable registration.

  7. A Model of Regularization Parameter Determination in Low-Dose X-Ray CT Reconstruction Based on Dictionary Learning.

    PubMed

    Zhang, Cheng; Zhang, Tao; Zheng, Jian; Li, Ming; Lu, Yanfei; You, Jiali; Guan, Yihui

    2015-01-01

    In recent years, X-ray computed tomography (CT) is becoming widely used to reveal patient's anatomical information. However, the side effect of radiation, relating to genetic or cancerous diseases, has caused great public concern. The problem is how to minimize radiation dose significantly while maintaining image quality. As a practical application of compressed sensing theory, one category of methods takes total variation (TV) minimization as the sparse constraint, which makes it possible and effective to get a reconstruction image of high quality in the undersampling situation. On the other hand, a preliminary attempt of low-dose CT reconstruction based on dictionary learning seems to be another effective choice. But some critical parameters, such as the regularization parameter, cannot be determined by detecting datasets. In this paper, we propose a reweighted objective function that contributes to a numerical calculation model of the regularization parameter. A number of experiments demonstrate that this strategy performs well with better reconstruction images and saving of a large amount of time.

  8. dPIRPLE: a joint estimation framework for deformable registration and penalized-likelihood CT image reconstruction using prior images

    NASA Astrophysics Data System (ADS)

    Dang, H.; Wang, A. S.; Sussman, Marc S.; Siewerdsen, J. H.; Stayman, J. W.

    2014-09-01

    Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration, and

  9. dPIRPLE: A Joint Estimation Framework for Deformable Registration and Penalized-Likelihood CT Image Reconstruction using Prior Images

    PubMed Central

    Dang, H.; Wang, A. S.; Sussman, Marc S.; Siewerdsen, J. H.; Stayman, J. W.

    2014-01-01

    Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc.). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration

  10. Evidence of dose saving in routine CT practice using iterative reconstruction derived from a national diagnostic reference level survey

    PubMed Central

    Hayton, A; Beveridge, T; Marks, P; Wallace, A

    2015-01-01

    Objective: To assess the influence and significance of the use of iterative reconstruction (IR) algorithms on patient dose in CT in Australia. Methods: We examined survey data submitted to the Australian Radiation Protection and Nuclear Safety Agency (ARPANSA) National Diagnostic Reference Level Service (NDRLS) during 2013 and 2014. We compared median survey dose metrics with categorization by scan region and use of IR. Results: The use of IR results in a reduction in volume CT dose index of between 17% and 44% and a reduction in dose–length product of between 14% and 34% depending on the specific scan region. The reduction was highly significant (p < 0.001, Wilcoxon rank-sum test) for all six scan regions included in the NDRLS. Overall, 69% (806/1167) of surveys included in the analysis used IR. Conclusion: The use of IR in CT is achieving dose savings of 20–30% in routine practice in Australia. IR appears to be widely used by participants in the ARPANSA NDRLS with approximately 70% of surveys submitted employing this technique. Advances in knowledge: This study examines the impact of the use of IR on patient dose in CT on a national scale. PMID:26133224

  11. Accelerating ordered subsets image reconstruction for X-ray CT using spatially non-uniform optimization transfer

    PubMed Central

    Kim, Donghwan; Pal, Debashish; Thibault, Jean-Baptiste; Fessler, Jeffrey A.

    2013-01-01

    Statistical image reconstruction algorithms in X-ray CT provide improved image quality for reduced dose levels but require substantial computation time. Iterative algorithms that converge in few iterations and that are amenable to massive parallelization are favorable in multiprocessor implementations. The separable quadratic surrogate (SQS) algorithm is desirable as it is simple and updates all voxels simultaneously. However, the standard SQS algorithm requires many iterations to converge. This paper proposes an extension of the SQS algorithm that leads to spatially non-uniform updates. The non-uniform (NU) SQS encourages larger step sizes for the voxels that are expected to change more between the current and the final image, accelerating convergence, while the derivation of NU-SQS guarantees monotonic descent. Ordered subsets (OS) algorithms can also accelerate SQS, provided suitable “subset balance” conditions hold. These conditions can fail in 3D helical cone-beam CT due to incomplete sampling outside the axial region-of-interest (ROI). This paper proposes a modified OS algorithm that is more stable outside the ROI in helical CT. We use CT scans to demonstrate that the proposed NU-OS-SQS algorithm handles the helical geometry better than the conventional OS methods and “converges” in less than half the time of ordinary OS-SQS. PMID:23751959

  12. Reconstruction of muscle fascicle architecture from iodine-enhanced microCT images: A combined texture mapping and streamline approach.

    PubMed

    Kupczik, Kornelius; Stark, Heiko; Mundry, Roger; Neininger, Fabian T; Heidlauf, Thomas; Röhrle, Oliver

    2015-10-07

    Skeletal muscle models are used to investigate motion and force generation in both biological and bioengineering research. Yet, they often lack a realistic representation of the muscle's internal architecture which is primarily composed of muscle fibre bundles, known as fascicles. Recently, it has been shown that fascicles can be resolved with micro-computed tomography (µCT) following staining of the muscle tissue with iodine potassium iodide (I2KI). Here, we present the reconstruction of the fascicular spatial arrangement and geometry of the superficial masseter muscle of a dog based on a combination of pattern recognition and streamline computation. A cadaveric head of a dog was incubated in I2KI and µCT-scanned. Following segmentation of the masseter muscle a statistical pattern recognition algorithm was applied to create a vector field of fascicle directions. Streamlines were then used to transform the vector field into a realistic muscle fascicle representation. The lengths of the reconstructed fascicles and the pennation angles in two planes (frontal and sagittal) were extracted and compared against a tracked fascicle field obtained through cadaver dissection. Both fascicle lengths and angles were found to vary substantially within the muscle confirming the complex and heterogeneous nature of skeletal muscle described by previous studies. While there were significant differences in the pennation angle between the experimentally derived and µCT-reconstructed data, there was congruence in the fascicle lengths. We conclude that the presented approach allows for embedding realistic fascicle information into finite element models of skeletal muscles to better understand the functioning of the musculoskeletal system.

  13. Cone-beam CT of traumatic brain injury using statistical reconstruction with a post-artifact-correction noise model

    NASA Astrophysics Data System (ADS)

    Dang, H.; Stayman, J. W.; Sisniega, A.; Xu, J.; Zbijewski, W.; Yorkston, J.; Aygun, N.; Koliatsos, V.; Siewerdsen, J. H.

    2015-03-01

    Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered back-projection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

  14. WE-EF-207-07: Dual Energy CT with One Full Scan and a Second Sparse-View Scan Using Structure Preserving Iterative Reconstruction (SPIR)

    SciTech Connect

    Wang, T; Zhu, L

    2015-06-15

    Purpose: Conventional dual energy CT (DECT) reconstructs CT and basis material images from two full-size projection datasets with different energy spectra. To relax the data requirement, we propose an iterative DECT reconstruction algorithm using one full scan and a second sparse-view scan by utilizing redundant structural information of the same object acquired at two different energies. Methods: We first reconstruct a full-scan CT image using filtered-backprojection (FBP) algorithm. The material similarities of each pixel with other pixels are calculated by an exponential function about pixel value differences. We assume that the material similarities of pixels remains in the second CT scan, although pixel values may vary. An iterative method is designed to reconstruct the second CT image from reduced projections. Under the data fidelity constraint, the algorithm minimizes the L2 norm of the difference between pixel value and its estimation, which is the average of other pixel values weighted by their similarities. The proposed algorithm, referred to as structure preserving iterative reconstruction (SPIR), is evaluated on physical phantoms. Results: On the Catphan600 phantom, SPIR-based DECT method with a second 10-view scan reduces the noise standard deviation of a full-scan FBP CT reconstruction by a factor of 4 with well-maintained spatial resolution, while iterative reconstruction using total-variation regularization (TVR) degrades the spatial resolution at the same noise level. The proposed method achieves less than 1% measurement difference on electron density map compared with the conventional two-full-scan DECT. On an anthropomorphic pediatric phantom, our method successfully reconstructs the complicated vertebra structures and decomposes bone and soft tissue. Conclusion: We develop an effective method to reduce the number of views and therefore data acquisition in DECT. We show that SPIR-based DECT using one full scan and a second 10-view scan can

  15. Combination of a low tube voltage technique with the hybrid iterative reconstruction (iDose) algorithm at coronary CT angiography

    PubMed Central

    Funama, Yoshinori; Taguchi, Katsuyuki; Utsunomiya, Daisuke; Oda, Seitaro; Yanaga, Yumi; Yamashita, Yasuyuki; Awai, Kazuo

    2011-01-01

    We compare the performance of low-tube voltage with the hybrid iterative reconstruction (iDose) with standard- and low-tube voltage with the filtered backprojection (FBP) using phantoms at CT coronary angiography (CTCA). At CTCA, application of the combined low-tube voltage with iDose resulted in significant image quality improvements compared to the low-tube voltage with FBP. Image quality was the same or better despite a reduction in the radiation dose by 76% compared with standard-tube voltage with FBP. PMID:21765305

  16. A three-stage method for the 3D reconstruction of the tracheobronchial tree from CT scans.

    PubMed

    Rosell, Jan; Cabras, Paolo

    2013-01-01

    This paper proposes a method for segmenting the airways from CT scans of the chest to obtain a 3D model that can be used in the virtual bronchoscopy for the exploration and the planning of paths to the lesions. The method is composed of 3 stages: a gross segmentation that reconstructs the main airway tree using adaptive region growing, a finer segmentation that identifies any potential airway region based on a 2D process that enhances bronchi walls using local information, and a final process to connect any isolated bronchus to the main airways using a morphologic reconstruction process and a path planning technique. The paper includes two examples for the evaluation and discussion of the proposal.

  17. Surgical Classification of the Mandibular Deformity in Craniofacial Microsomia Using 3-Dimensional Computed Tomography

    PubMed Central

    Swanson, Jordan W.; Mitchell, Brianne T.; Wink, Jason A.; Taylor, Jesse A.

    2016-01-01

    Background: Grading systems of the mandibular deformity in craniofacial microsomia (CFM) based on conventional radiographs have shown low interrater reproducibility among craniofacial surgeons. We sought to design and validate a classification based on 3-dimensional CT (3dCT) that correlates features of the deformity with surgical treatment. Methods: CFM mandibular deformities were classified as normal (T0), mild (hypoplastic, likely treated with orthodontics or orthognathic surgery; T1), moderate (vertically deficient ramus, likely treated with distraction osteogenesis; T2), or severe (ramus rudimentary or absent, with either adequate or inadequate mandibular body bone stock; T3 and T4, likely treated with costochondral graft or free fibular flap, respectively). The 3dCT face scans of CFM patients were randomized and then classified by craniofacial surgeons. Pairwise agreement and Fleiss' κ were used to assess interrater reliability. Results: The 3dCT images of 43 patients with CFM (aged 0.1–15.8 years) were reviewed by 15 craniofacial surgeons, representing an average 15.2 years of experience. Reviewers demonstrated fair interrater reliability with average pairwise agreement of 50.4 ± 9.9% (Fleiss' κ = 0.34). This represents significant improvement over the Pruzansky–Kaban classification (pairwise agreement, 39.2%; P = 0.0033.) Reviewers demonstrated substantial interrater reliability with average pairwise agreement of 83.0 ± 7.6% (κ = 0.64) distinguishing deformities requiring graft or flap reconstruction (T3 and T4) from others. Conclusion: The proposed classification, designed for the era of 3dCT, shows improved consensus with respect to stratifying the severity of mandibular deformity and type of operative management. PMID:27104097

  18. Image quality of CT angiography with model-based iterative reconstruction in young children with congenital heart disease: comparison with filtered back projection and adaptive statistical iterative reconstruction.

    PubMed

    Son, Sung Sil; Choo, Ki Seok; Jeon, Ung Bae; Jeon, Gye Rok; Nam, Kyung Jin; Kim, Tae Un; Yeom, Jeong A; Hwang, Jae Yeon; Jeong, Dong Wook; Lim, Soo Jin

    2015-06-01

    To retrospectively evaluate the image quality of CT angiography (CTA) reconstructed by model-based iterative reconstruction (MBIR) and to compare this with images obtained by filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) in newborns and infants with congenital heart disease (CHD). Thirty-seven children (age 4.8 ± 3.7 months; weight 4.79 ± 0.47 kg) with suspected CHD underwent CTA on a 64detector MDCT without ECG gating (80 kVp, 40 mA using tube current modulation). Total dose length product was recorded in all patients. Images were reconstructed using FBP, ASIR, and MBIR. Objective image qualities (density, noise) were measured in the great vessels and heart chambers. The contrast-to-noise ratio (CNR) was calculated by measuring the density and noise of myocardial walls. Two radiologists evaluated images for subjective noise, diagnostic confidence, and sharpness at the level prior to the first branch of the main pulmonary artery. Images were compared with respect to reconstruction method, and reconstruction times were measured. Images from all patients were diagnostic, and the effective dose was 0.22 mSv. The objective image noise of MBIR was significantly lower than those of FBP and ASIR in the great vessels and heart chambers (P < 0.05); however, with respect to attenuations in the four chambers, ascending aorta, descending aorta, and pulmonary trunk, no statistically significant difference was observed among the three methods (P > 0.05). Mean CNR values were 8.73 for FBP, 14.54 for ASIR, and 22.95 for MBIR. In addition, the subjective image noise of MBIR was significantly lower than those of the others (P < 0.01). Furthermore, while FBP had the highest score for image sharpness, ASIR had the highest score for diagnostic confidence (P < 0.05), and mean reconstruction times were 5.1 ± 2.3 s for FBP and ASIR and 15.1 ± 2.4 min for MBIR. While CTA with MBIR in newborns and infants with CHD can reduce image noise and

  19. Feature constrained compressed sensing CT image reconstruction from incomplete data via robust principal component analysis of the database.

    PubMed

    Wu, Dufan; Li, Liang; Zhang, Li

    2013-06-21

    In computed tomography (CT), incomplete data problems such as limited angle projections often cause artifacts in the reconstruction results. Additional prior knowledge of the image has shown the potential for better results, such as a prior image constrained compressed sensing algorithm. While a pre-full-scan of the same patient is not always available, massive well-reconstructed images of different patients can be easily obtained from clinical multi-slice helical CTs. In this paper, a feature constrained compressed sensing (FCCS) image reconstruction algorithm was proposed to improve the image quality by using the prior knowledge extracted from the clinical database. The database consists of instances which are similar to the target image but not necessarily the same. Robust principal component analysis is employed to retrieve features of the training images to sparsify the target image. The features form a low-dimensional linear space and a constraint on the distance between the image and the space is used. A bi-criterion convex program which combines the feature constraint and total variation constraint is proposed for the reconstruction procedure and a flexible method is adopted for a good solution. Numerical simulations on both the phantom and real clinical patient images were taken to validate our algorithm. Promising results are shown for limited angle problems.

  20. A sparsity-based iterative algorithm for reconstruction of micro-CT images from highly undersampled projection datasets obtained with a synchrotron X-ray source

    NASA Astrophysics Data System (ADS)

    Melli, S. Ali; Wahid, Khan A.; Babyn, Paul; Cooper, David M. L.; Gopi, Varun P.

    2016-12-01

    Synchrotron X-ray Micro Computed Tomography (Micro-CT) is an imaging technique which is increasingly used for non-invasive in vivo preclinical imaging. However, it often requires a large number of projections from many different angles to reconstruct high-quality images leading to significantly high radiation doses and long scan times. To utilize this imaging technique further for in vivo imaging, we need to design reconstruction algorithms that reduce the radiation dose and scan time without reduction of reconstructed image quality. This research is focused on using a combination of gradient-based Douglas-Rachford splitting and discrete wavelet packet shrinkage image denoising methods to design an algorithm for reconstruction of large-scale reduced-view synchrotron Micro-CT images with acceptable quality metrics. These quality metrics are computed by comparing the reconstructed images with a high-dose reference image reconstructed from 1800 equally spaced projections spanning 180°. Visual and quantitative-based performance assessment of a synthetic head phantom and a femoral cortical bone sample imaged in the biomedical imaging and therapy bending magnet beamline at the Canadian Light Source demonstrates that the proposed algorithm is superior to the existing reconstruction algorithms. Using the proposed reconstruction algorithm to reduce the number of projections in synchrotron Micro-CT is an effective way to reduce the overall radiation dose and scan time which improves in vivo imaging protocols.

  1. SU-E-I-04: Improving CT Quality for Radiation Therapy of Patients with High Body Mass Index Using Iterative Reconstruction Algorithms

    SciTech Connect

    Noid, G; Tai, A; Li, X

    2015-06-15

    Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. The CT IQ for patients with a high Body Mass Index (BMI) can suffer from increased noise due to photon starvation. The purpose of this study is to investigate and to quantify the IQ enhancement for high BMI patients through the application of IR algorithms. Methods: CT raw data collected for 6 radiotherapy (RT) patients with BMI, greater than or equal to 30 were retrospectively analyzed. All CT data were acquired using a CT scanner (Somaton Definition AS Open, Siemens) installed in a linac room (CT-on-rails) using standard imaging protocols. The CT data were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared and correlated with patient depth and BMI. The patient depth was defined as the largest distance from anterior to posterior along the bilateral symmetry axis. Results: IR techniques are demonstrated to preserve contrast and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is roughly doubled by adopting the highest SAFIRE strength. A significant correlation was observed between patient depth and IR noise reduction through Pearson’s correlation test (R = 0.9429/P = 0.0167). The mean patient depth was 30.4 cm and the average relative noise reduction for the strongest iterative reconstruction was 55%. Conclusion: The IR techniques produce a measureable enhancement to CT IQ by reducing the noise. Dramatic noise reduction is evident for the high BMI patients. The improved CT IQ enables more accurate delineation of tumors and organs at risk and more accuarte dose calculations for RT planning and delivery guidance. Supported by Siemens.

  2. Technical Note: Measuring contrast- and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging

    SciTech Connect

    Yu, Lifeng Vrieze, Thomas J.; Leng, Shuai; Fletcher, Joel G.; McCollough, Cynthia H.

    2015-05-15

    Purpose: The spatial resolution of iterative reconstruction (IR) in computed tomography (CT) is contrast- and noise-dependent because of the nonlinear regularization. Due to the severe noise contamination, it is challenging to perform precise spatial-resolution measurements at very low-contrast levels. The purpose of this study was to measure the spatial resolution of a commercially available IR method using ensemble-averaged images acquired from repeated scans. Methods: A low-contrast phantom containing three rods (7, 14, and 21 HU below background) was scanned on a 128-slice CT scanner at three dose levels (CTDI{sub vol} = 16, 8, and 4 mGy). Images were reconstructed using two filtered-backprojection (FBP) kernels (B40 and B20) and a commercial IR method (sinogram affirmed iterative reconstruction, SAFIRE, Siemens Healthcare) with two strength settings (I40-3 and I40-5). The same scan was repeated 100 times at each dose level. The modulation transfer function (MTF) was calculated based on the edge profile measured on the ensemble-averaged images. Results: The spatial resolution of the two FBP kernels, B40 and B20, remained relatively constant across contrast and dose levels. However, the spatial resolution of the two IR kernels degraded relative to FBP as contrast or dose level decreased. For a given dose level at 16 mGy, the MTF{sub 50%} value normalized to the B40 kernel decreased from 98.4% at 21 HU to 88.5% at 7 HU for I40-3 and from 97.6% to 82.1% for I40-5. At 21 HU, the relative MTF{sub 50%} value decreased from 98.4% at 16 mGy to 90.7% at 4 mGy for I40-3 and from 97.6% to 85.6% for I40-5. Conclusions: A simple technique using ensemble averaging from repeated CT scans can be used to measure the spatial resolution of IR techniques in CT at very low contrast levels. The evaluated IR method degraded the spatial resolution at low contrast and high noise levels.

  3. WE-AB-204-01: Performance Characterization of Regularized-Reconstruction Algorithm for 90Y PET/CT Images

    SciTech Connect

    Siman, W; Kappadath, S; Mawlawi, O

    2015-06-15

    Purpose: {sup 90}Y PET/CT imaging and quantification have recently been suggested as an approach of treatment verification. However, due to low positron yield (32ppm), the {sup 90}Y-PET/CT images are very noisy. Iterative reconstruction techniques that employ regularization, e.g. block sequential regularized expectation maximization (BSREM) algorithm (recently implemented on GE scanners – QClear™), has the potential to increase quantitative accuracy with lower noise penalty compared to OSEM. Our aim is to investigate the performance of RR algorithms in {sup 90}Y PET/CT studies. Methods: A NEMA IEC phantom filled with 3GBq {sup 90}YCl{sub 2} (to simulate patient treatment) was imaged on GE-D690 for 1800s/bed. The sphere-to-background ratio of 7. The data were reconstructed using OSEM and BSREM with PSF modeling and TOF correction while varying the iterations (IT) from 1–6 with fixed 24subsets. For BSREM, the edge-preservation parameter (γ ) was 2 and the penalty-parameters (β) was varied 350–950. In all cases a post-reconstruction filter of 5.2mm (2pixel) transaxial and standard z-axis were used. Sphere average activity concentration (AC) and background standard deviation (SD) were then calculated from VOIs drawn in the spheres and background. Results: Increasing IT from 1to6, the %SD in OSEM increased from 30% to 80%, whereas %SD in BSREM images increased by <5% for all βs. BSREM with β=350 didn’t offer any improvement over OSEM (convergence of mean achieved at 2 IT, in this study). Increasing β from 350 to 950 reduced the AC accuracy of small spheres (<20mm) by 10% and noise from 40% to 20%, which resulted in CNR increase from 11 to 17. Conclusion: In count-limited studies such as {sup 90}Y PET/CT, BSREM can be used to suppress image noise and increase CNR at the expense of a relatively small decrease of quantitative accuracy. The BSREM parameters need to be optimized for each study depending on the radionuclides and count densities. Research

  4. SU-E-I-86: Ultra-Low Dose Computed Tomography Attenuation Correction for Pediatric PET CT Using Adaptive Statistical Iterative Reconstruction (ASiR™)

    SciTech Connect

    Brady, S; Shulkin, B

    2015-06-15

    Purpose: To develop ultra-low dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultra-low doses (10–35 mAs). CT quantitation: noise, low-contrast resolution, and CT numbers for eleven tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% CTDIvol (0.39/3.64; mGy) radiation dose from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUVbw) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation organ dose, as derived from patient exam size specific dose estimate (SSDE), was converted to effective dose using the standard ICRP report 103 method. Effective dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative patient population dose reduction and noise control. Results: CT numbers were constant to within 10% from the non-dose reduced CTAC image down to 90% dose reduction. No change in SUVbw, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols reconstructed with ASiR and down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62%–86% (3.2/8.3−0.9/6.2; mSv). Noise magnitude in dose-reduced patient images increased but was not statistically different from pre dose-reduced patient images. Conclusion: Using ASiR allowed for aggressive reduction in CTAC dose with no change in PET reconstructed images while maintaining sufficient image quality for co

  5. Variability in CT lung-nodule quantification: Effects of dose reduction and reconstruction methods on density and texture based features

    PubMed Central

    Lo, P.; Young, S.; Kim, H. J.; Brown, M. S.

    2016-01-01

    Purpose: To investigate the effects of dose level and reconstruction method on density and texture based features computed from CT lung nodules. Methods: This study had two major components. In the first component, a uniform water phantom was scanned at three dose levels and images were reconstructed using four conventional filtered backprojection (FBP) and four iterative reconstruction (IR) methods for a total of 24 different combinations of acquisition and reconstruction conditions. In the second component, raw projection (sinogram) data were obtained for 33 lung nodules from patients scanned as a part of their clinical practice, where low dose acquisitions were simulated by adding noise to sinograms acquired at clinical dose levels (a total of four dose levels) and reconstructed using one FBP kernel and two IR kernels for a total of 12 conditions. For the water phantom, spherical regions of interest (ROIs) were created at multiple locations within the water phantom on one reference image obtained at a reference condition. For the lung nodule cases, the ROI of each nodule was contoured semiautomatically (with manual editing) from images obtained at a reference condition. All ROIs were applied to their corresponding images reconstructed at different conditions. For 17 of the nodule cases, repeat contours were performed to assess repeatability. Histogram (eight features) and gray level co-occurrence matrix (GLCM) based texture features (34 features) were computed for all ROIs. For the lung nodule cases, the reference condition was selected to be 100% of clinical dose with FBP reconstruction using the B45f kernel; feature values calculated from other conditions were compared to this reference condition. A measure was introduced, which the authors refer to as Q, to assess the stability of features across different conditions, which is defined as the ratio of reproducibility (across conditions) to repeatability (across repeat contours) of each feature. Results: The

  6. Quantitative image reconstruction for dual-isotope parathyroid SPECT/CT: phantom experiments and sample patient studies

    NASA Astrophysics Data System (ADS)

    Shcherbinin, S.; Chamoiseau, S.; Celler, A.

    2012-08-01

    We investigated the quantitative accuracy of the model-based dual-isotope single-photon emission computed tomography (DI-SPECT) reconstructions that use Klein-Nishina expressions to estimate the scattered photon contributions to the projection data. Our objective was to examine the ability of the method to recover the absolute activities pertaining to both radiotracers: Tc-99m and I-123. We validated our method through a series of phantom experiments performed using a clinical hybrid SPECT/CT camera (Infinia Hawkeye, GE Healthcare). Different activity ratios and different attenuating media were used in these experiments to create cross-talk effects of varying severity, which can occur in clinical studies. Accurate model-based corrections for scatter and cross-talk with CT attenuation maps allowed for the recovery of the absolute activities from DI-SPECT/CT scans with errors that ranged 0-10% for both radiotracers. The unfavorable activity ratios increased the computational burden but practically did not affect the resulting accuracy. The visual analysis of parathyroid patient data demonstrated that our model-based processing improved adenoma/background contrast and enhanced localization of small or faint adenomas.

  7. SU-D-207-04: GPU-Based 4D Cone-Beam CT Reconstruction Using Adaptive Meshing Method

    SciTech Connect

    Zhong, Z; Gu, X; Iyengar, P; Mao, W; Wang, J; Guo, X

    2015-06-15

    Purpose: Due to the limited number of projections at each phase, the image quality of a four-dimensional cone-beam CT (4D-CBCT) is often degraded, which decreases the accuracy of subsequent motion modeling. One of the promising methods is the simultaneous motion estimation and image reconstruction (SMEIR) approach. The objective of this work is to enhance the computational speed of the SMEIR algorithm using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step is to generate the tetrahedral mesh based on the features of a reference phase 4D-CBCT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. After the mesh generation, the updated motion model and other phases of 4D-CBCT can be obtained by matching the 4D-CBCT projection images at each phase with the corresponding forward projections of the deformed reference phase of 4D-CBCT. The entire process of this 4D-CBCT reconstruction method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its tremendous parallel computing ability. Results: A 4D XCAT digital phantom was used to test the proposed mesh-based image reconstruction algorithm. The image Result shows both bone structures and inside of the lung are well-preserved and the tumor position can be well captured. Compared to the previous voxel-based CPU implementation of SMEIR, the proposed method is about 157 times faster for reconstructing a 10 -phase 4D-CBCT with dimension 256×256×150. Conclusion: The GPU-based parallel 4D CBCT reconstruction method uses the feature-based mesh for estimating motion model and demonstrates equivalent image Result with previous voxel-based SMEIR approach, with significantly improved computational speed.

  8. High-resolution secondary reconstructions with the use of flat panel CT in the clinical assessment of patients with cochlear implants.

    PubMed

    Pearl, M S; Roy, A; Limb, C J

    2014-06-01

    Radiologic assessment of cochlear implants can be limited because of metallic streak artifacts and the high attenuation of the temporal bones. We report on 14 patients with 18 cochlear implants (17 Med-El standard 31.5-mm arrays, 1 Med-El medium 24-mm array) who underwent flat panel CT with the use of high-resolution secondary reconstruction techniques. Flat panel CT depicted the insertion site, cochlear implant course, and all 216 individual electrode contacts. The calculated mean angular insertion depth for standard arrays was 591.9° (SD = 70.9; range, 280°). High-resolution secondary reconstructions of the initial flat panel CT dataset, by use of a manually generated field of view, Hounsfield unit kernel type, and sharp image characteristics, provided high-quality images with improved spatial resolution. Flat panel CT is a promising imaging tool for the postoperative evaluation of cochlear implant placement.

  9. SU-E-J-99: Reconstruction of Cone Beam CT Image Using Volumetric Modulated Arc Therapy Exit Beams

    SciTech Connect

    Jeong, K; Goddard, L; Savacool, M; Mynampati, D; Godoy Scripes, P; Tome', W; Kuo, H; Basavatia, A; Hong, L; Yaparpalvi, R; Kalnicki, S

    2014-06-01

    Purpose: To test the possibility of obtaining an image of the treated volume during volumetric modulated arc therapy (VMAT) with exit beams. Method: Using a Varian Clinac 21EX and MVCT detector the following three sets of detector projection data were obtained for cone beam CT reconstruction with and without a Catphan 504 phantom. 1) 72 projection images from 20 × 16 cm{sup 2} open beam with 3 MUs, 2) 72 projection images from 20 × 16 cm{sup 2} MLC closed beam with 14 MUs. 3) 137 projection images from a test RapicArc QA plan. All projection images were obtained in ‘integrated image’ mode. We used OSCaR code to reconstruct the cone beam CT images. No attempts were made to reduce scatter or artifacts. Results: With projection set 1) we obtained a good quality MV CBCT image by optimizing the reconstruction parameters. Using projection set 2) we were not able to obtain a CBCT image of the phantom, which was determined to be due to the variation of interleaf leakage with gantry angle. From projection set 3), we were able to obtain a weak but meaningful signal in the image, especially in the target area where open beam signals were dominant. This finding suggests that one might be able to acquire CBCT images with rough body shape and some details inside the irradiated target area. Conclusion: Obtaining patient images using the VMAT exit beam is challenging but possible. We were able to determine sources of image degradation such as gantry angle dependent interleaf leakage and beams with a large scatter component. We are actively working on improving image quality.

  10. A clinical evaluation of total variation-Stokes image reconstruction strategy for low-dose CT imaging of the chest

    NASA Astrophysics Data System (ADS)

    Liu, Yan; Zhang, Hao; Moore, William; Bhattacharji, Priya; Liang, Zhengrong

    2015-03-01

    One hundred "normal-dose" computed tomography (CT) studies of the chest (i.e., 1,160 projection views, 120kVp, 100mAs) data sets were acquired from the patients who were scheduled for lung biopsy at Stony Brook University Hospital under informed consent approved by our Institutional Review Board. To mimic low-dose CT imaging scenario (i.e., sparse-view scan), sparse projection views were evenly extracted from the total 1,160 projections of each patient and the total radiation dose was reduced according to how many sparse views were selected. A standard filtered backprojection (FBP) algorithm was applied to the 1160 projections to produce reference images for comparison purpose. In the low-dose scenario, both the FBP and total variation-stokes (TVS) algorithms were applied to reconstruct the corresponding low-dose images. The reconstructed images were evaluated by an experienced thoracic radiologist against the reference images. Both the low-dose reconstructions and the reference images were displayed on a 4- megapixel monitor in soft tissue and lung windows. The images were graded by a five-point scale from 0 to 4 (0, nondiagnostic; 1, severe artifact with low confidence; 2, moderate artifact or moderate diagnostic confidences; 3, mild artifact or high confidence; 4, well depicted without artifacts). Quantitative evaluation measurements such as standard deviations for different tissue types and universal quality index were also studied and reported for the results. The evaluation concluded that the TVS can reduce the view number from 1,160 to 580 with slightly lower scores as the reference, resulting in a dose reduction to close 50%.

  11. SU-E-J-147: Monte Carlo Study of the Precision and Accuracy of Proton CT Reconstructed Relative Stopping Power Maps

    SciTech Connect

    Dedes, G; Asano, Y; Parodi, K; Arbor, N; Dauvergne, D; Testa, E; Letang, J; Rit, S

    2015-06-15

    Purpose: The quantification of the intrinsic performances of proton computed tomography (pCT) as a modality for treatment planning in proton therapy. The performance of an ideal pCT scanner is studied as a function of various parameters. Methods: Using GATE/Geant4, we simulated an ideal pCT scanner and scans of several cylindrical phantoms with various tissue equivalent inserts of different sizes. Insert materials were selected in order to be of clinical relevance. Tomographic images were reconstructed using a filtered backprojection algorithm taking into account the scattering of protons into the phantom. To quantify the performance of the ideal pCT scanner, we study the precision and the accuracy with respect to the theoretical relative stopping power ratios (RSP) values for different beam energies, imaging doses, insert sizes and detector positions. The planning range uncertainty resulting from the reconstructed RSP is also assessed by comparison with the range of the protons in the analytically simulated phantoms. Results: The results indicate that pCT can intrinsically achieve RSP resolution below 1%, for most examined tissues at beam energies below 300 MeV and for imaging doses around 1 mGy. RSP maps accuracy of less than 0.5 % is observed for most tissue types within the studied dose range (0.2–1.5 mGy). Finally, the uncertainty in the proton range due to the accuracy of the reconstructed RSP map is well below 1%. Conclusion: This work explores the intrinsic performance of pCT as an imaging modality for proton treatment planning. The obtained results show that under ideal conditions, 3D RSP maps can be reconstructed with an accuracy better than 1%. Hence, pCT is a promising candidate for reducing the range uncertainties introduced by the use of X-ray CT alongside with a semiempirical calibration to RSP.Supported by the DFG Cluster of Excellence Munich-Centre for Advanced Photonics (MAP)

  12. Respiratory-gated segment reconstruction for radiation treatment planning using 256-slice CT-scanner during free breathing

    NASA Astrophysics Data System (ADS)

    Mori, Shinichiro; Endo, Masahiro; Kohno, Ryosuke; Minohara, Shinichi; Kohno, Kazutoshi; Asakura, Hiroshi; Fujiwara, Hideaki; Murase, Kenya

    2005-04-01

    The conventional respiratory-gated CT scan technique includes anatomic motion induced artifacts due to the low temporal resolution. They are a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Temporal resolution and image quality are important factors to minimize planning target volume margin due to the respiratory motion. To achieve high temporal resolution and high signal-to-noise ratio, we developed a respiratory gated segment reconstruction algorithm and adapted it to Feldkamp-Davis-Kress algorithm (FDK) with a 256-detector row CT. The 256-detector row CT could scan approximately 100 mm in the cranio-caudal direction with 0.5 mm slice thickness in one rotation. Data acquisition for the RS-FDK relies on the assistance of the respiratory sensing system by a cine scan mode (table remains stationary). We evaluated RS-FDK in phantom study with the 256-detector row CT and compared it with full scan (FS-FDK) and HS-FDK results with regard to volume accuracy and image noise, and finally adapted the RS-FDK to an animal study. The RS-FDK gave a more accurate volume than the others and it had the same signal-to-noise ratio as the FS-FDK. In the animal study, the RS-FDK visualized the clearest edges of the liver and pulmonary vessels of all the algorithms. In conclusion, the RS-FDK algorithm has a capability of high temporal resolution and high signal-to-noise ratio. Therefore it will be useful when combined with new radiotherapy techniques including image guided radiation therapy (IGRT) and 4D radiation therapy.

  13. Effect of light source instability on uniformity of 3D reconstructions from a cone beam optical CT scanner.

    PubMed

    Begg, J; Taylor, M L; Holloway, L; Kron, T; Franich, R D

    2014-12-01

    Temporally varying light intensity during acquisition of projection images in an optical CT scanner can potentially be misinterpreted as physical properties of the sample. This work investigated the impact of LED light source intensity instability on measured attenuation coefficients. Different scenarios were investigated by conducting one or both of the reference and data scans in a 'cold' scanner, where the light source intensity had not yet stabilised. Uniform samples were scanned to assess the impact on measured uniformity. The orange (590 nm) light source decreased in intensity by 29 % over the first 2 h, while the red (633 nm) decreased by 9 %. The rates of change of intensity at 2 h were 0.1 and 0.03 % respectively over a 5 min period-corresponding to the scan duration. The normalisation function of the reconstruction software does not fully account for the intensity differences and discrepancies remain. Attenuation coefficient inaccuracies of up to 8 % were observed for data reconstructed from projection images acquired with a cold scanner. Increased noise was observed for most cases where one or both of the scans was acquired without sufficient warm-up. The decrease in accuracy and increase in noise were most apparent for data reconstructed from reference and data scans acquired with a cold scanner on different days.

  14. WE-G-207-04: Non-Local Total-Variation (NLTV) Combined with Reweighted L1-Norm for Compressed Sensing Based CT Reconstruction

    SciTech Connect

    Kim, H; Chen, J; Pouliot, J

    2015-06-15

    Purpose: Compressed sensing (CS) has been used for CT (4DCT/CBCT) reconstruction with few projections to reduce dose of radiation. Total-variation (TV) in L1-minimization (min.) with local information is the prevalent technique in CS, while it can be prone to noise. To address the problem, this work proposes to apply a new image processing technique, called non-local TV (NLTV), to CS based CT reconstruction, and incorporate reweighted L1-norm into it for more precise reconstruction. Methods: TV minimizes intensity variations by considering two local neighboring voxels, which can be prone to noise, possibly damaging the reconstructed CT image. NLTV, contrarily, utilizes more global information by computing a weight function of current voxel relative to surrounding search area. In fact, it might be challenging to obtain an optimal solution due to difficulty in defining the weight function with appropriate parameters. Introducing reweighted L1-min., designed for approximation to ideal L0-min., can reduce the dependence on defining the weight function, therefore improving accuracy of the solution. This work implemented the NLTV combined with reweighted L1-min. by Split Bregman Iterative method. For evaluation, a noisy digital phantom and a pelvic CT images are employed to compare the quality of images reconstructed by TV, NLTV and reweighted NLTV. Results: In both cases, conventional and reweighted NLTV outperform TV min. in signal-to-noise ratio (SNR) and root-mean squared errors of the reconstructed images. Relative to conventional NLTV, NLTV with reweighted L1-norm was able to slightly improve SNR, while greatly increasing the contrast between tissues due to additional iterative reweighting process. Conclusion: NLTV min. can provide more precise compressed sensing based CT image reconstruction by incorporating the reweighted L1-norm, while maintaining greater robustness to the noise effect than TV min.

  15. Cervical vertebrae maturation index estimates on cone beam CT: 3D reconstructions vs sagittal sections

    PubMed Central

    Bonfim, Marco A E; Costa, André L F; Ximenez, Michel E L; Cotrim-Ferreira, Flávio A; Ferreira-Santos, Rívea I

    2016-01-01

    Objectives: The aim of this study was to evaluate the performance of CBCT three-dimensional (3D) reconstructions and sagittal sections for estimates of cervical vertebrae maturation index (CVMI). Methods: The sample consisted of 72 CBCT examinations from patients aged 8–16 years (45 females and 27 males) selected from the archives of two private clinics. Two calibrated observers (kappa scores: ≥0.901) interpreted the CBCT settings twice. Intra- and interobserver agreement for both imaging exhibition modes was analyzed by kappa statistics, which was also used to analyze the agreement between 3D reconstructions and sagittal sections. Correlations between cervical vertebrae maturation estimates and chronological age, as well as between the assessments by 3D reconstructions and sagittal sections, were analyzed using gamma Goodman–Kruskal coefficients (α = 0.05). Results: The kappa scores evidenced almost perfect agreement between the first and second assessments of the cervical vertebrae by 3D reconstructions (0.933–0.983) and sagittal sections (0.983–1.000). Similarly, the agreement between 3D reconstructions and sagittal sections was almost perfect (kappa index: 0.983). In most divergent cases, the difference between 3D reconstructions and sagittal sections was one stage of CVMI. Strongly positive correlations (>0.8, p < 0.001) were found not only between chronological age and CVMI but also between the estimates by 3D reconstructions and sagittal sections (p < 0.001). Conclusions: Although CBCT imaging must not be used exclusively for this purpose, it may be suitable for skeletal maturity assessments. PMID:26509559

  16. Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance

    SciTech Connect

    Li, Ke; Chen, Guang-Hong; Garrett, John; Ge, Yongshuai

    2014-07-15

    Purpose: Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. Methods: The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDI{sub vol} =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIR (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d′. Results: (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than

  17. Iterative CT reconstruction using coordinate descent with ordered subsets of data

    NASA Astrophysics Data System (ADS)

    Noo, F.; Hahn, K.; Schöndube, H.; Stierstorfer, K.

    2016-04-01

    Image reconstruction based on iterative minimization of a penalized weighted least-square criteria has become an important topic of research in X-ray computed tomography. This topic is motivated by increasing evidence that such a formalism may enable a significant reduction in dose imparted to the patient while maintaining or improving image quality. One important issue associated with this iterative image reconstruction concept is slow convergence and the associated computational effort. For this reason, there is interest in finding methods that produce approximate versions of the targeted image with a small number of iterations and an acceptable level of discrepancy. We introduce here a novel method to produce such approximations: ordered subsets in combination with iterative coordinate descent. Preliminary results demonstrate that this method can produce, within 10 iterations and using only a constant image as initial condition, satisfactory reconstructions that retain the noise properties of the targeted image.

  18. Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis

    PubMed Central

    Jun, Kyungtaek; Yoon, Seokhwan

    2017-01-01

    Since X-ray tomography is now widely adopted in many different areas, it becomes more crucial to find a robust routine of handling tomographic data to get better quality of reconstructions. Though there are several existing techniques, it seems helpful to have a more automated method to remove the possible errors that hinder clearer image reconstruction. Here, we proposed an alternative method and new algorithm using the sinogram and the fixed point. An advanced physical concept of Center of Attenuation (CA) was also introduced to figure out how this fixed point is applied to the reconstruction of image having errors we categorized in this article. Our technique showed a promising performance in restoring images having translation and vertical tilt errors. PMID:28120881

  19. Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis

    NASA Astrophysics Data System (ADS)

    Jun, Kyungtaek; Yoon, Seokhwan

    2017-01-01

    Since X-ray tomography is now widely adopted in many different areas, it becomes more crucial to find a robust routine of handling tomographic data to get better quality of reconstructions. Though there are several existing techniques, it seems helpful to have a more automated method to remove the possible errors that hinder clearer image reconstruction. Here, we proposed an alternative method and new algorithm using the sinogram and the fixed point. An advanced physical concept of Center of Attenuation (CA) was also introduced to figure out how this fixed point is applied to the reconstruction of image having errors we categorized in this article. Our technique showed a promising performance in restoring images having translation and vertical tilt errors.

  20. GPU-based iterative cone-beam CT reconstruction using tight frame regularization

    NASA Astrophysics Data System (ADS)

    Jia, Xun; Dong, Bin; Lou, Yifei; Jiang, Steve B.

    2011-07-01

    The x-ray imaging dose from serial cone-beam computed tomography (CBCT) scans raises a clinical concern in most image-guided radiation therapy procedures. It is the goal of this paper to develop a fast graphic processing unit (GPU)-based algorithm to reconstruct high-quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose. For this purpose, we have developed an iterative tight-frame (TF)-based CBCT reconstruction algorithm. A condition that a real CBCT image has a sparse representation under a TF basis is imposed in the iteration process as regularization to the solution. To speed up the computation, a multi-grid method is employed. Our GPU implementation has achieved high computational efficiency and a CBCT image of resolution 512 × 512 × 70 can be reconstructed in ~5 min. We have tested our algorithm on a digital NCAT phantom and a physical Catphan phantom. It is found that our TF-based algorithm is able to reconstruct CBCT in the context of undersampling and low mAs levels. We have also quantitatively analyzed the reconstructed CBCT image quality in terms of the modulation-transfer function and contrast-to-noise ratio under various scanning conditions. The results confirm the high CBCT image quality obtained from our TF algorithm. Moreover, our algorithm has also been validated in a real clinical context using a head-and-neck patient case. Comparisons of the developed TF algorithm and the current state-of-the-art TV algorithm have also been made in various cases studied in terms of reconstructed image quality and computation efficiency.

  1. Dose reconstruction for volumetric modulated arc therapy (VMAT) using cone-beam CT and dynamic log files

    NASA Astrophysics Data System (ADS)

    Qian, Jianguo; Lee, Louis; Liu, Wu; Chu, Karen; Mok, Edward; Luxton, Gary; Le, Quynh-Thu; Xing, Lei

    2010-07-01

    Volumetric modulated arc therapy (VMAT) has recently emerged as a new clinical modality for conformal radiation therapy. The aim of this work is to establish a methodology and procedure for retrospectively reconstructing the actual dose delivered in VMAT based on the pre-treatment cone-beam computed tomography (CBCT) and dynamic log files. CBCT was performed before the dose delivery and the system's log files were retrieved after the delivery. Actual delivery at a control point including MLC leaf positions, gantry angles and cumulative monitor units (MUs) was recorded in the log files and the information was extracted using in-house developed software. The extracted information was then embedded into the original treatment DICOM-radiation therapy (RT) file to replace the original control point parameters. This reconstituted DICOM-RT file was imported into the Eclipse treatment planning system (TPS) and dose was computed on the corresponding CBCT. A series of phantom experiments was performed to show the feasibility of dose reconstruction, validate the procedure and demonstrate the efficacy of this methodology. The resultant dose distributions and dose-volume histograms (DVHs) were compared with those of the original treatment plan. The studies indicated that CBCT-based VMAT dose reconstruction is readily achievable and provides a valuable tool for monitoring the dose actually delivered to the tumor target as well as the sensitive structures. In the absence of setup errors, the reconstructed dose shows no significant difference from the original pCT-based plan. It is also elucidated that the proposed method is capable of revealing the dosimetric changes in the presence of setup errors. The method reported here affords an objective means for dosimetric evaluation of VMAT delivery and is useful for adaptive VMAT in future. This work was presented at the 2009 Annual Meeting of AAPM, Anaheim, CA.

  2. Dose reconstruction for volumetric modulated arc therapy (VMAT) using cone-beam CT and dynamic log files.

    PubMed

    Qian, Jianguo; Lee, Louis; Liu, Wu; Chu, Karen; Mok, Edward; Luxton, Gary; Le, Quynh-Thu; Xing, Lei

    2010-07-07

    Volumetric modulated arc therapy (VMAT) has recently emerged as a new clinical modality for conformal radiation therapy. The aim of this work is to establish a methodology and procedure for retrospectively reconstructing the actual dose delivered in VMAT based on the pre-treatment cone-beam computed tomography (CBCT) and dynamic log files. CBCT was performed before the dose delivery and the system's log files were retrieved after the delivery. Actual delivery at a control point including MLC leaf positions, gantry angles and cumulative monitor units (MUs) was recorded in the log files and the information was extracted using in-house developed software. The extracted information was then embedded into the original treatment DICOM-radiation therapy (RT) file to replace the original control point parameters. This reconstituted DICOM-RT file was imported into the Eclipse treatment planning system (TPS) and dose was computed on the corresponding CBCT. A series of phantom experiments was performed to show the feasibility of dose reconstruction, validate the procedure and demonstrate the efficacy of this methodology. The resultant dose distributions and dose-volume histograms (DVHs) were compared with those of the original treatment plan. The studies indicated that CBCT-based VMAT dose reconstruction is readily achievable and provides a valuable tool for monitoring the dose actually delivered to the tumor target as well as the sensitive structures. In the absence of setup errors, the reconstructed dose shows no significant difference from the original pCT-based plan. It is also elucidated that the proposed method is capable of revealing the dosimetric changes in the presence of setup errors. The method reported here affords an objective means for dosimetric evaluation of VMAT delivery and is useful for adaptive VMAT in future.

  3. Myocardial blood flow measurement with a conventional dual-head SPECT/CT with spatiotemporal iterative reconstructions - a clinical feasibility study

    PubMed Central

    Alhassen, Fares; Nguyen, Nhan; Bains, Sukhkarn; Gould, Robert G; Seo, Youngho; Bacharach, Stephen L; Song, Xiyun; Shao, Lingxiong; Gullberg, Grant T; Aparici, Carina Mari

    2014-01-01

    Cardiac single photon emission computed tomography (SPECT) cameras typically rotate too slowly around a patient to capture changes in the blood pool activity distribution and provide accurate kinetic parameters. A spatiotemporal iterative reconstruction method to overcome these limitations was investigated. Dynamic rest/stress 99mTc-methoxyisobutylisonitrile (99mTc-MIBI) SPECT/CT was performed along with reference standard rest/stress dynamic positron emission tomography (PET/CT) 13N-NH3 in five patients. The SPECT data were reconstructed using conventional and spatiotemporal iterative reconstruction methods. The spatiotemporal reconstruction yielded improved image quality, defined here as a statistically significant (p<0.01) 50% contrast enhancement. We did not observe a statistically significant difference between the correlations of the conventional and spatiotemporal SPECT myocardial uptake K 1 values with PET K 1 values (r=0.25, 0.88, respectively) (p<0.17). These results indicate the clinical feasibility of quantitative, dynamic SPECT/CT using 99mTc-MIBI and warrant further investigation. Spatiotemporal reconstruction clearly provides an advantage over a conventional reconstruction in computing K 1. PMID:24380045

  4. Image quality evaluation of iterative CT reconstruction algorithms: a perspective from spatial domain noise texture measures

    NASA Astrophysics Data System (ADS)

    Pachon, Jan H.; Yadava, Girijesh; Pal, Debashish; Hsieh, Jiang

    2012-03-01

    Non-linear iterative reconstruction (IR) algorithms have shown promising improvements in image quality at reduced dose levels. However, IR images sometimes may be perceived as having different image noise texture than traditional filtered back projection (FBP) reconstruction. Standard linear-systems-based image quality evaluation metrics are limited in characterizing such textural differences and non-linear image-quality vs. dose trade-off behavior, hence limited in predicting potential impact of such texture differences in diagnostic task. In an attempt to objectively characterize and measure dose dependent image noise texture and statistical properties of IR and FBP images, we have investigated higher order moments and Haralicks Gray Level Co-occurrence Matrices (GLCM) based texture features on phantom images reconstructed by an iterative and a traditional FBP method. In this study, the first 4 central order moments, and multiple texture features from Haralick GLCM in 4 directions at 6 different ROI sizes and four dose levels were computed. For resolution, noise and texture trade-off analysis, spatial frequency domain NPS and contrastdependent MTF were also computed. Preliminary results of the study indicate that higher order moments, along with spatial domain measures of energy, contrast, correlation, homogeneity, and entropy consistently capture the textural differences between FBP and IR as dose changes. These metrics may be useful in describing the perceptual differences in randomness, coarseness, contrast, and smoothness of images reconstructed by non-linear algorithms.

  5. WE-G-207-02: Full Sequential Projection Onto Convex Sets (FS-POCS) for X-Ray CT Reconstruction

    SciTech Connect

    Liu, L; Han, Y; Jin, M

    2015-06-15

    Purpose: To develop an iterative reconstruction method for X-ray CT, in which the reconstruction can quickly converge to the desired solution with much reduced projection views. Methods: The reconstruction is formulated as a convex feasibility problem, i.e. the solution is an intersection of three convex sets: 1) data fidelity (DF) set – the L2 norm of the difference of observed projections and those from the reconstructed image is no greater than an error bound; 2) non-negativity of image voxels (NN) set; and 3) piecewise constant (PC) set - the total variation (TV) of the reconstructed image is no greater than an upper bound. The solution can be found by applying projection onto convex sets (POCS) sequentially for these three convex sets. Specifically, the algebraic reconstruction technique and setting negative voxels as zero are used for projection onto the DF and NN sets, respectively, while the projection onto the PC set is achieved by solving a standard Rudin, Osher, and Fatemi (ROF) model. The proposed method is named as full sequential POCS (FS-POCS), which is tested using the Shepp-Logan phantom and the Catphan600 phantom and compared with two similar algorithms, TV-POCS and CP-TV. Results: Using the Shepp-Logan phantom, the root mean square error (RMSE) of reconstructed images changing along with the number of iterations is used as the convergence measurement. In general, FS- POCS converges faster than TV-POCS and CP-TV, especially with fewer projection views. FS-POCS can also achieve accurate reconstruction of cone-beam CT of the Catphan600 phantom using only 54 views, comparable to that of FDK using 364 views. Conclusion: We developed an efficient iterative reconstruction for sparse-view CT using full sequential POCS. The simulation and physical phantom data demonstrated the computational efficiency and effectiveness of FS-POCS.

  6. Total Variation-Stokes Strategy for Sparse-View X-ray CT Image Reconstruction

    PubMed Central

    Liu, Yan; Ma, Jianhua; Lu, Hongbing; Wang, Ke; Zhang, Hao; Moore, William

    2014-01-01

    Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and/or other constraints, a piecewise-smooth X-ray computed tomography image can be reconstructed from sparse-view projection data. However, due to the piecewise constant assumption for the TV model, the reconstructed images are frequently reported to suffer from the blocky or patchy artifacts. To eliminate this drawback, we present a total variation-stokes-projection onto convex sets (TVS-POCS) reconstruction method in this paper. The TVS model is derived by introducing isophote directions for the purpose of recovering possible missing information in the sparse-view data situation. Thus the desired consistencies along both the normal and the tangent directions are preserved in the resulting images. Compared to the previous TV-based image reconstruction algorithms, the preserved consistencies by the TVS-POCS method are expected to generate noticeable gains in terms of eliminating the patchy artifacts and preserving subtle structures. To evaluate the presented TVS-POCS method, both qualitative and quantitative studies were performed using digital phantom, physical phantom and clinical data experiments. The results reveal that the presented method can yield images with several noticeable gains, measured by the universal quality index and the full-width-at-half-maximum merit, as compared to its corresponding TV-based algorithms. In addition, the results further indicate that the TVS-POCS method approaches to the gold standard result of the filtered back-projection reconstruction in the full-view data case as theoretically expected, while most previous iterative methods may fail in the full-view case because of their artificial textures in the results. PMID:24595347

  7. Model-Based Iterative Reconstruction for Dual-Energy X-Ray CT Using a Joint Quadratic Likelihood Model.

    PubMed

    Zhang, Ruoqiao; Thibault, Jean-Baptiste; Bouman, Charles A; Sauer, Ken D; Hsieh, Jiang

    2014-01-01

    Dual-energy X-ray CT (DECT) has the potential to improve contrast and reduce artifacts as compared to traditional CT. Moreover, by applying model-based iterative reconstruction (MBIR) to dual-energy data, one might also expect to reduce noise and improve resolution. However, the direct implementation of dual-energy MBIR requires the use of a nonlinear forward model, which increases both complexity and computation. Alternatively, simplified forward models have been used which treat the material-decomposed channels separately, but these approaches do not fully account for the statistical dependencies in the channels. In this paper, we present a method for joint dual-energy MBIR (JDE-MBIR), which simplifies the forward model while still accounting for the complete statistical dependency in the material-decomposed sinogram components. The JDE-MBIR approach works by using a quadratic approximation to the polychromatic log-likelihood and a simple but exact nonnegativity constraint in the image domain. We demonstrate that our method is particularly effective when the DECT system uses fast kVp switching, since in this case the model accounts for the inaccuracy of interpolated sinogram entries. Both phantom and clinical results show that the proposed model produces images that compare favorably in quality to previous decomposition-based methods, including FBP and other statistical iterative approaches.

  8. Computed tomographic-dacryocystography (CT-DCG) of the normal canine nasolacrimal drainage system with three-dimensional reconstruction.

    PubMed

    Rached, Paula A; Canola, Júlio C; Schlüter, Claudia; Laus, José L; Oechtering, Gerhard; de Almeida, Denise E; Ludewig, Eberhard

    2011-05-01

    The aims of the study were (1) to quantify the influence of selected imaging parameters on the image quality (slice thickness, mAs, and beam orientation) defining optimal conditions for scan protocols and (2) to evaluate the benefits of the 3D reconstruction techniques for visualization of NDS structures in dogs. CT-DCG was performed bilaterally in 32 heads of dogs. CT transverse images were obtained using a combination of two slice thickness values (0.8 mm and 2 mm) and two mAs values (50 mAs and 300 mAs). Two beam projection orientations were also tested: transverse plane (perpendicular to the hard palate) and oblique to the hard palate. Three-dimensional images were obtained using Volume Rendering (VR). Transverse beam projection proved to be superior for the assessment of the inferior and superior lacrimal canaliculi and lacrimal sac. In this study, there was no statistical difference regarding mAs values (50 mAs and 300 mAs) and slice thickness values (0.8 mm and 2 mm). Three-dimensional images were helpful for the assessment of topographic relationship between nasolacrimal structures and cranial landmarks.

  9. Numerical investigation of ultrasonic attenuation through 2D trabecular bone structures reconstructed from CT scans and random realizations.

    PubMed

    Gilbert, Robert P; Guyenne, Philippe; Li, Jing

    2014-02-01

    In this paper, we compare ultrasound interrogations of actual CT-scanned images of trabecular bone with artificial randomly constructed bone. Even though it is known that actual bone does not have randomly distributed trabeculae, we find that the ultrasound attenuations are close enough to cast doubt on any microstructural information, such as trabeculae width and distance between trabeculae, being gleaned from such experiments. More precisely, we perform numerical simulations of ultrasound interrogation on cancellous bone to investigate the phenomenon of ultrasound attenuation as a function of excitation frequency and bone porosity. The theoretical model is based on acoustic propagation equations for a composite fluid-solid material and is solved by a staggered-grid finite-difference scheme in the time domain. Numerical experiments are performed on two-dimensional bone samples reconstructed from CT-scanned images of real human calcaneus and from random distributions of fluid-solid particles generated via the turning bands method. A detailed comparison is performed on various parameters such as the attenuation rate and speed of sound through the bone samples as well as the normalized broadband ultrasound attenuation coefficient. Comparing results from these two types of bone samples allows us to assess the role of bone microstructure in ultrasound attenuation. It is found that the random model provides suitable bone samples for ultrasound interrogation in the transverse direction of the trabecular network.

  10. Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

    PubMed Central

    Xu, Qiaofeng; Yang, Deshan; Tan, Jun; Sawatzky, Alex; Anastasio, Mark A.

    2016-01-01

    Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated

  11. Analyses of sexual dimorphism of contemporary Japanese using reconstructed three-dimensional CT images--curvature of the best-fit circle of the greater sciatic notch.

    PubMed

    Biwasaka, Hitoshi; Aoki, Yasuhiro; Tanijiri, Toyohisa; Sato, Kei; Fujita, Sachiko; Yoshioka, Kunihiro; Tomabechi, Makiko

    2009-04-01

    We examined various expression methods of sexual dimorphism of the greater sciatic notch (GSN) of the pelvis in contemporary Japanese residents by analyzing the three-dimensional (3D) images reconstructed by multi-slice computed tomography (CT) data, using image-processing and measurement software. Mean error of anthropological measurement values between two skeletonized pelves and their reconstructed 3D-CT images was 1.4%. A spline curve was set along the edge of the GSN of reconstructed pelvic 3D-CT images. Then a best-fit circle for subsets of the spline curve, 5-60mm in length and passing through the deepest point (inflection point) of the GSN, was created, and the radius of the circle (curvature radius) and its ratio to the maximum pelvic height (curvature quotient) were computed. In analysis of images reconstructed from CT data of 180 individuals (male: 91, female: 89), sexes were correctly identified in with 89.4% of specimens, with a spline curve length of 60mm. Because sexing was possible even in deeper regions of the GSN, which are relatively resistant to postmortem damage, the present method may be useful for practical forensic investigation.

  12. TV-regularized iterative image reconstruction on a mobile C-ARM CT

    NASA Astrophysics Data System (ADS)

    Pan, Yongsheng; Whitaker, Ross; Cheryauka, Arvi; Ferguson, Dave

    2010-04-01

    3D computed tomography has been extensively studied and widely used in modern society. Although most manufacturers choose the filtered backprojection algorithm (FBP) for its accuracy and efficiency, iterative reconstruction methods have a significant potential to provide superior performance for incomplete, noisy projection data. However, iterative methods have a high computational cost, which hinders their practical use. Furthermore, regularization is usually required to reduce the effects of noise. In this paper, we analyze the use of the Simultaneous Algebraic Reconstruction Technique (SART) with total variation (TV) regularization. Additionally, graphics hardware is utilized to increase the speed of SART. NVIDIA's GPU and Compute Unified Device Architecture (CUDA) comprise the core of our computational platform. GPU implementation details, including ray-based forward projection and voxel-based backprojection are illustrated. Experimental results for high-resolution synthetic and real data are provided to demonstrate the accuracy and efficiency of the proposed framework.

  13. Four-dimensional cone beam CT reconstruction and enhancement using a temporal nonlocal means method

    SciTech Connect

    Jia Xun; Tian Zhen; Lou Yifei; Sonke, Jan-Jakob; Jiang, Steve B.

    2012-09-15

    Purpose: Four-dimensional cone beam computed tomography (4D-CBCT) has been developed to provide respiratory phase-resolved volumetric imaging in image guided radiation therapy. Conventionally, it is reconstructed by first sorting the x-ray projections into multiple respiratory phase bins according to a breathing signal extracted either from the projection images or some external surrogates, and then reconstructing a 3D CBCT image in each phase bin independently using FDK algorithm. This method requires adequate number of projections for each phase, which can be achieved using a low gantry rotation or multiple gantry rotations. Inadequate number of projections in each phase bin results in low quality 4D-CBCT images with obvious streaking artifacts. 4D-CBCT images at different breathing phases share a lot of redundant information, because they represent the same anatomy captured at slightly different temporal points. Taking this redundancy along the temporal dimension into account can in principle facilitate the reconstruction in the situation of inadequate number of projection images. In this work, the authors propose two novel 4D-CBCT algorithms: an iterative reconstruction algorithm and an enhancement algorithm, utilizing a temporal nonlocal means (TNLM) method. Methods: The authors define a TNLM energy term for a given set of 4D-CBCT images. Minimization of this term favors those 4D-CBCT images such that any anatomical features at one spatial point at one phase can be found in a nearby spatial point at neighboring phases. 4D-CBCT reconstruction is achieved by minimizing a total energy containing a data fidelity term and the TNLM energy term. As for the image enhancement, 4D-CBCT images generated by the FDK algorithm are enhanced by minimizing the TNLM function while keeping the enhanced images close to the FDK results. A forward-backward splitting algorithm and a Gauss-Jacobi iteration method are employed to solve the problems. The algorithms implementation on

  14. Four-dimensional cone beam CT reconstruction and enhancement using a temporal nonlocal means method

    PubMed Central

    Jia, Xun; Tian, Zhen; Lou, Yifei; Sonke, Jan-Jakob; Jiang, Steve B.

    2012-01-01

    Purpose: Four-dimensional cone beam computed tomography (4D-CBCT) has been developed to provide respiratory phase-resolved volumetric imaging in image guided radiation therapy. Conventionally, it is reconstructed by first sorting the x-ray projections into multiple respiratory phase bins according to a breathing signal extracted either from the projection images or some external surrogates, and then reconstructing a 3D CBCT image in each phase bin independently using FDK algorithm. This method requires adequate number of projections for each phase, which can be achieved using a low gantry rotation or multiple gantry rotations. Inadequate number of projections in each phase bin results in low quality 4D-CBCT images with obvious streaking artifacts. 4D-CBCT images at different breathing phases share a lot of redundant information, because they represent the same anatomy captured at slightly different temporal points. Taking this redundancy along the temporal dimension into account can in principle facilitate the reconstruction in the situation of inadequate number of projection images. In this work, the authors propose two novel 4D-CBCT algorithms: an iterative reconstruction algorithm and an enhancement algorithm, utilizing a temporal nonlocal means (TNLM) method. Methods: The authors define a TNLM energy term for a given set of 4D-CBCT images. Minimization of this term favors those 4D-CBCT images such that any anatomical features at one spatial point at one phase can be found in a nearby spatial point at neighboring phases. 4D-CBCT reconstruction is achieved by minimizing a total energy containing a data fidelity term and the TNLM energy term. As for the image enhancement, 4D-CBCT images generated by the FDK algorithm are enhanced by minimizing the TNLM function while keeping the enhanced images close to the FDK results. A forward–backward splitting algorithm and a Gauss–Jacobi iteration method are employed to solve the problems. The algorithms implementation

  15. An innovative strategy for the identification and 3D reconstruction of pancreatic cancer from CT images.

    PubMed

    Marconi, S; Pugliese, L; Del Chiaro, M; Pozzi Mucelli, R; Auricchio, F; Pietrabissa, A

    2016-09-01

    We propose an innovative tool for Pancreatic Ductal AdenoCarcinoma 3D reconstruction from Multi-Detector-Computed Tomography. The tumor mass is discriminated from health tissue, and the resulting segmentation labels are rendered preserving information on different hypodensity levels. The final 3D virtual model includes also pancreas and main peri-pancreatic vessels, and it is suitable for 3D printing. We performed a preliminary evaluation of the tool effectiveness presenting ten cases of Pancreatic Ductal AdenoCarcinoma processed with the tool to an expert radiologist who can correct the result of the discrimination. In seven of ten cases, the 3D reconstruction is accepted without any modification, while in three cases, only 1.88, 5.13, and 5.70 %, respectively, of the segmentation labels are modified, preliminary proving the high effectiveness of the tool.

  16. Direct reconstruction in CT-analogous pharmacokinetic diffuse fluorescence tomography: two-dimensional simulative and experimental validations

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Zhang, Yanqi; Zhang, Limin; Li, Jiao; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng

    2016-04-01

    We present a generalized strategy for direct reconstruction in pharmacokinetic diffuse fluorescence tomography (DFT) with CT-analogous scanning mode, which can accomplish one-step reconstruction of the indocyanine-green pharmacokinetic-rate images within in vivo small animals by incorporating the compartmental kinetic model into an adaptive extended Kalman filtering scheme and using an instantaneous sampling dataset. This scheme, compared with the established indirect and direct methods, eliminates the interim error of the DFT inversion and relaxes the expensive requirement of the instrument for obtaining highly time-resolved date-sets of complete 360 deg projections. The scheme is validated by two-dimensional simulations for the two-compartment model and pilot phantom experiments for the one-compartment model, suggesting that the proposed method can estimate the compartmental concentrations and the pharmacokinetic-rates simultaneously with a fair quantitative and localization accuracy, and is well suitable for cost-effective and dense-sampling instrumentation based on the highly-sensitive photon counting technique.

  17. Investigation of optimal parameters for penalized maximum-likelihood reconstruction applied to iodinated contrast-enhanced breast CT

    NASA Astrophysics Data System (ADS)

    Makeev, Andrey; Ikejimba, Lynda; Lo, Joseph Y.; Glick, Stephen J.

    2016-03-01

    Although digital mammography has reduced breast cancer mortality by approximately 30%, sensitivity and specificity are still far from perfect. In particular, the performance of mammography is especially limited for women with dense breast tissue. Two out of every three biopsies performed in the U.S. are unnecessary, thereby resulting in increased patient anxiety, pain, and possible complications. One promising tomographic breast imaging method that has recently been approved by the FDA is dedicated breast computed tomography (BCT). However, visualizing lesions with BCT can still be challenging for women with dense breast tissue due to the minimal contrast for lesions surrounded by fibroglandular tissue. In recent years there has been renewed interest in improving lesion conspicuity in x-ray breast imaging by administration of an iodinated contrast agent. Due to the fully 3-D imaging nature of BCT, as well as sub-optimal contrast enhancement while the breast is under compression with mammography and breast tomosynthesis, dedicated BCT of the uncompressed breast is likely to offer the best solution for injected contrast-enhanced x-ray breast imaging. It is well known that use of statistically-based iterative reconstruction in CT results in improved image quality at lower radiation dose. Here we investigate possible improvements in image reconstruction for BCT, by optimizing free regularization parameter in method of maximum likelihood and comparing its performance with clinical cone-beam filtered backprojection (FBP) algorithm.

  18. Reconstruction of limited-angle dual-energy CT using mutual learning and cross-estimation (MLCE)

    NASA Astrophysics Data System (ADS)

    Zhang, Huayu; Xing, Yuxiang

    2016-03-01

    Dual-energy CT (DECT) imaging has gained a lot of attenuation because of its capability to discriminate materials. We proposes a flexible DECT scan strategy which can be realized on a system with general X-ray sources and detectors. In order to lower dose and scanning time, our DECT acquires two projections data sets on two arcs of limited-angular coverage (one for each energy) respectively. Meanwhile, a certain number of rays from two data sets form conjugate sampling pairs. Our reconstruction method for such a DECT scan mainly tackles the consequent limited-angle problem. Using the idea of artificial neural network, we excavate the connection between projections at two different energies by constructing a relationship between the linear attenuation coefficient of the high energy and that of the low one. We use this relationship to cross-estimate missing projections and reconstruct attenuation images from an augmented data set including projections at views covered by itself (projections collected in scanning) and by the other energy (projections estimated) for each energy respectively. Validated by our numerical experiment on a dental phantom with rather complex structures, our DECT is effective in recovering small structures in severe limited-angle situations. This DECT scanning strategy can much broaden DECT design in reality.

  19. Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study.

    PubMed

    Lu, Wenting; Yan, Hao; Gu, Xuejun; Tian, Zhen; Luo, Ouyang; Yang, Liu; Zhou, Linghong; Cervino, Laura; Wang, Jing; Jiang, Steve; Jia, Xun

    2014-10-21

    With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSEs) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3-6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1-3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART.

  20. Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study

    NASA Astrophysics Data System (ADS)

    Lu, Wenting; Yan, Hao; Gu, Xuejun; Tian, Zhen; Ouyang, Luo; Yang, Liu; Zhou, Linghong; Cervino, Laura; Wang, Jing; Jiang, Steve; Jia, Xun

    2014-10-01

    With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSEs) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3-6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1-3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART.

  1. Reconstructing Cone-beam CT with Spatially Varying Qualities for Adaptive Radiotherapy, a Proof-of-Principle Study1

    PubMed Central

    Lu, Wenting; Yan, Hao; Gu, Xuejun; Tian, Zhen; Luo, Ouyang; Yang, Liu; Zhou, Linghong; Cervino, Laura; Wang, Jing; Jiang, Steve; Jia, Xun

    2014-01-01

    With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSE) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3–6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1–3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART. PMID:25255957

  2. Evaluation of the resolving potency of a novel reconstruction filter on periodontal ligament space with dental cone-beam CT: a quantitative phantom study

    NASA Astrophysics Data System (ADS)

    Houno, Yuuki; Hishikawa, Toshimitsu; Gotoh, Ken-ichi; Naitoh, Munetaka; Ariji, Eiichiro; Kodera, Yoshie

    2014-03-01

    Diagnosis of the alveolar bone condition is important for the treatment planning of periodontal disease. Especially the determination of periodontal ligament space is the most important remark because it represents the periodontal tissue support for tooth retention. However, owing to the image blur of the current cone-beam CT (CBCT) imaging technique, the periodontal ligament space is difficult to visualize. In this study, we developed an original periodontal ligament phantom (PLP) and evaluated the image quality of simulated periodontal ligament space using a novel reconstruction filter for CBCT that emphasized high frequency component. PLP was composed from two resin blocks of different materials, the bone equivalent block and the dentine equivalent block. They were assembled to make continuously changing space from 0.0 to 1.0 millimeter that mimics periodontal ligament space. PLP was placed in water and the image was obtained by using Alphard-3030 dental cone-beam CT (Asahi Roentgen Industry Co., Ltd.). Then we reconstructed the projection data with a novel reconstruction filter. The axial images were compared with conventional reconstructed images. In novel filter reconstruction images, 0.4 millimeter of the space width was steadily detected by calculation of pixel value, on the other hand 0.6 millimeter was in conventional images. With our method, the resolving potency of conebeam CT images was improved.

  3. Total variation minimization-based spiral CT reconstruction in a dental panoramic imaging system for cost-effective, low-dose dental X-ray imaging

    NASA Astrophysics Data System (ADS)

    Hong, D. K.; Lee, S. H.; Cho, H. S.; Oh, J. E.; Lee, M. S.; Kim, H. J.; Park, Y. O.; Je, U. K.; Choi, S. I.; Koo, Y. S.; Cho, H. M.

    2012-12-01

    In the paper, we proposed a pragmatic method capable of implementing a cost-effective, low-dose CT reconstruction directly onto a dental panoramic X-ray imaging system by adopting a spiral source trajectory. In the proposed geometry, a linear-type panoramic imaging sensor is rotated 90° from the orientation for panoramic imaging to imitate fan-beam image acquisition. For image reconstruction, we considered a total variation (TV) minimization-based algorithm that exploited the sparsity of the image gradient and was capable of reconstructing CT images with substantially high image accuracy against the image artifacts from sparse-view data. We implemented the algorithm for the proposed geometry and performed systematic simulation works to demonstrate its feasibility for dental imaging applications. CT images were successfully reconstructed from the proposed geometry, and the reconstruction quality was evaluated quantitatively by using an image similarity metric. We expect the proposed method to be applicable to developing a cost-effective, low-dose, all-in-one dental imaging system.

  4. Low-Dose High-Pitch CT Angiography of the Supraaortic Arteries Using Sinogram-Affirmed Iterative Reconstruction

    PubMed Central

    Beitzke, Dietrich; Nolz, Richard; Unterhumer, Sylvia; Plank, Christina; Weber, Michael; Schernthaner, Rüdiger; Schöpf, Veronika; Wolf, Florian; Loewe, Christian

    2014-01-01

    Objective To prospectively evaluate image quality and radiation dose using a low-dose computed tomography angiography protocol and iterative image reconstruction for high-pitch dual-source CT-angiography (DSCTA) of the supraaortic arteries. Material and Methods DSCTA was performed in 42 patients, using either 120 kVp tube voltage, 120 mAS tube current, 2.4 pitch and filtered back projection, or 100 kVp tube voltage, 100 mAs tube current, 3.2 pitch, and sinogram affirmed iterative reconstruction. Measurements of vessel attenuation, of the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) were performed to objectively evaluate image quality. Two readers evaluated subjective image quality and image noise, using a four-point scale. Effective dose was used to compare the differences in radiation dose. Results Low-dose protocol application showed significantly higher vessel opacification (p = 0.013), and non-significantly higher CNR and SNR values. There was no difference in the subjective image quality and image noise reading between the protocols. Effective dose was significantly lower using the low-dose protocol (1.29±0.21 mSv vs. 2.92±0.72 mSv; p<0.001). Conclusion The combined use of reduced tube voltage, reduced tube current, and iterative reconstruction reduces radiation dose by 55.4% in high-pitch DSCTA of the supraaortic arteries without impairment of image quality. PMID:24919195

  5. Multi-resolution statistical image reconstruction for mitigation of truncation effects: application to cone-beam CT of the head

    NASA Astrophysics Data System (ADS)

    Dang, Hao; Webster Stayman, J.; Sisniega, Alejandro; Zbijewski, Wojciech; Xu, Jennifer; Wang, Xiaohui; Foos, David H.; Aygun, Nafi; Koliatsos, Vassilis E.; Siewerdsen, Jeffrey H.

    2017-01-01

    A prototype cone-beam CT (CBCT) head scanner featuring model-based iterative reconstruction (MBIR) has been recently developed and demonstrated the potential for reliable detection of acute intracranial hemorrhage (ICH), which is vital to diagnosis of traumatic brain injury and hemorrhagic stroke. However, data truncation (e.g. due to the head holder) can result in artifacts that reduce image uniformity and challenge ICH detection. We propose a multi-resolution MBIR method with an extended reconstruction field of view (RFOV) to mitigate truncation effects in CBCT of the head. The image volume includes a fine voxel size in the (inner) nontruncated region and a coarse voxel size in the (outer) truncated region. This multi-resolution scheme allows extension of the RFOV to mitigate truncation effects while introducing minimal increase in computational complexity. The multi-resolution method was incorporated in a penalized weighted least-squares (PWLS) reconstruction framework previously developed for CBCT of the head. Experiments involving an anthropomorphic head phantom with truncation due to a carbon-fiber holder were shown to result in severe artifacts in conventional single-resolution PWLS, whereas extending the RFOV within the multi-resolution framework strongly reduced truncation artifacts. For the same extended RFOV, the multi-resolution approach reduced computation time compared to the single-resolution approach (viz. time reduced by 40.7%, 83.0%, and over 95% for an image volume of 6003, 8003, 10003 voxels). Algorithm parameters (e.g. regularization strength, the ratio of the fine and coarse voxel size, and RFOV size) were investigated to guide reliable parameter selection. The findings provide a promising method for truncation artifact reduction in CBCT and may be useful for other MBIR methods and applications for which truncation is a challenge.

  6. SU-E-I-82: Improving CT Image Quality for Radiation Therapy Using Iterative Reconstruction Algorithms and Slightly Increasing Imaging Doses

    SciTech Connect

    Noid, G; Chen, G; Tai, A; Li, X

    2014-06-01

    Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. For CT in radiation therapy (RT), slightly increasing imaging dose to improve IQ may be justified if it can substantially enhance structure delineation. The purpose of this study is to investigate and to quantify the IQ enhancement as a result of increasing imaging doses and using IR algorithms. Methods: CT images were acquired for phantoms, built to evaluate IQ metrics including spatial resolution, contrast and noise, with a variety of imaging protocols using a CT scanner (Definition AS Open, Siemens) installed inside a Linac room. Representative patients were scanned once the protocols were optimized. Both phantom and patient scans were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and the Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared. Results: IR techniques are demonstrated to preserve spatial resolution as measured by the point spread function and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is doubled by adopting the highest SAFIRE strength. As expected, increasing imaging dose reduces noise for both SAFIRE and FBP reconstructions. The contrast to noise increases from 3 to 5 by increasing the dose by a factor of 4. Similar IQ improvement was observed on the CTs for selected patients with pancreas and prostrate cancers. Conclusion: The IR techniques produce a measurable enhancement to CT IQ by reducing the noise. Increasing imaging dose further reduces noise independent of the IR techniques. The improved CT enables more accurate delineation of tumors and/or organs at risk during RT planning and delivery guidance.

  7. SU-E-I-93: Improved Imaging Quality for Multislice Helical CT Via Sparsity Regularized Iterative Image Reconstruction Method Based On Tensor Framelet

    SciTech Connect

    Nam, H; Guo, M; Lee, K; Li, R; Xing, L; Gao, H

    2014-06-01

    Purpose: Inspired by compressive sensing, sparsity regularized iterative reconstruction method has been extensively studied. However, its utility pertinent to multislice helical 4D CT for radiotherapy with respect to imaging quality, dose, and time has not been thoroughly addressed. As the beginning of such an investigation, this work carries out the initial comparison of reconstructed imaging quality between sparsity regularized iterative method and analytic method through static phantom studies using a state-of-art 128-channel multi-slice Siemens helical CT scanner. Methods: In our iterative method, tensor framelet (TF) is chosen as the regularization method for its superior performance from total variation regularization in terms of reduced piecewise-constant artifacts and improved imaging quality that has been demonstrated in our prior work. On the other hand, X-ray transforms and its adjoints are computed on-the-fly through GPU implementation using our previous developed fast parallel algorithms with O(1) complexity per computing thread. For comparison, both FDK (approximate analytic method) and Katsevich algorithm (exact analytic method) are used for multislice helical CT image reconstruction. Results: The phantom experimental data with different imaging doses were acquired using a state-of-art 128-channel multi-slice Siemens helical CT scanner. The reconstructed image quality was compared between TF-based iterative method, FDK and Katsevich algorithm with the quantitative analysis for characterizing signal-to-noise ratio, image contrast, and spatial resolution of high-contrast and low-contrast objects. Conclusion: The experimental results suggest that our tensor framelet regularized iterative reconstruction algorithm improves the helical CT imaging quality from FDK and Katsevich algorithm for static experimental phantom studies that have been performed.

  8. The Value of SPECT/CT in Monitoring Prefabricated Tissue-Engineered Bone and Orthotopic rhBMP-2 Implants for Mandibular Reconstruction

    PubMed Central

    Zhou, Miao; Peng, Xin; Mao, Chi; Tian, Jia-he; Zhang, Shu-wen; Xu, Fang; Tu, Jing-jing; Liu, Sheng; Hu, Min; Yu, Guang-yan

    2015-01-01

    Bone tissue engineering shows good prospects for mandibular reconstruction. In recent studies, prefabricated tissue-engineered bone (PTEB) by recombinant human bone morphogenetic proteins (rhBMPs) applied in vivo has found to be an effective alternative for autologous bone grafts. However, the optimal time to transfer PTEB for mandibular reconstruction is still not elucidated. Thus, here in an animal experiment of rhesus monkey, the suitable transferring time for PTEB to reconstruct mandibular defects was evaluated by 99mTc-MDP SPECT/CT, and its value in monitoring orthotopic rhBMP-2 implants for mandibular reconstruction was also evaluated. The result of SPECT/CT showed higher 99mTc-MDP uptake, indicating osteoinductivity, in rhBMP-2 incorporated demineralized freeze-dried bone allograft (DFDBA) and coralline hydroxyapatite (CHA) implants than those without BMP stimulation. 99mTc-MDP uptake of rhBMP-2 implant peaked at 8 weeks following implantation while CT showed the density of these implants increased after 13 weeks’ prefabrication. Histology confirmed that mandibular defects were repaired successfully with PTEB or orthotopically rhBMP-2 incorporated CHA implants, in accordance with SPECT/CT findings. Collectively, data shows 99mTc-MDP SPECT/CT is a sensitive and noninvasive tool to monitor osteoinductivity and bone regeneration of PTEB and orthotopic implants. The PTEB achieved peak osteoinductivity and bone density at 8 to 13 weeks following ectopic implantation, which would serve as a recommendable time frame for its transfer to mandibular reconstruction. PMID:26340447

  9. Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT

    PubMed Central

    Chen, Guang-Hong; Li, Yinsheng

    2015-01-01

    Purpose: In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. Methods: In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial–temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial–temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial–temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity

  10. An investigation of the iterative reconstruction method iDose4 on a Philips CT Brilliance 64 using a Catphan 600 phantom

    NASA Astrophysics Data System (ADS)

    Olsson, Marie-Louise; Norrgren, Kristina

    2012-03-01

    The number of CT examinations giving a relatively high patient exposure is increasing. It is therefore important to optimize the imaging conditions at these investigations. Many steps have been taken to reduce the radiation doses in CT examinations. Currently much work is related to iterative image reconstruction methods as alternative to the filtered back projection method. The aim of this work was to evaluate quality parameters in images from a CT (Philips Brilliance 64) equipped with the iterative reconstruction method iDose4 using a Catphan 600 phantom with and without body simulating ring. CT scans using abdomen protocol were taken with various tube currents and tube voltage and keeping collimation and pitch unchanged for all scans. All collected data were reconstructed with different levels of iDose4 (Level 2, 4, 6) and traditional filtered back projection. Image quality parameters were evaluated using AutoQA Lite TM (Version 2.3 2007 Iris QA, LLC). Results from the study shows that the iterative reconstruction method decreases the noise with 15-45% compared with filtered back projection depending on which level of iDose4 is used. The percentage reduction in noise level is the same with and without body simulating ring. Low contrast was improved with iDose4 and spatial resolution is only marginally affected by the method of reconstruction. However by reducing the image noise, the detectability can be improved. Our conclusion is that there is great potential to reduce the noise and thereby improve the image quality by using iterative reconstruction methods. This can also be used to lower radiation dose and maintain image quality or improve image quality.

  11. Task-Based Design of Fluence Field Modulation in CT for Model-Based Iterative Reconstruction.

    PubMed

    Gang, Grace J; Siewerdsen, Jeffrey H; Stayman, J Webster

    2016-07-01

    A task-driven imaging framework for prospective fluence field modulation (FFM) is developed in this paper. The design approach uses a system model that includes a parameterized FFM acquisition and model-based iterative reconstruction (MBIR) for image formation. Using prior anatomical knowledge (e.g. from a low-dose 3D scout image), accurate predictions of spatial resolution and noise as a function of FFM are integrated into a task-based objective function. Specifically, detectability index (d'), a common metric for task-based image quality assessment, is computed for a specific formulation of the imaging task. To optimize imaging performance in across an image volume, a maximin objective function was adopted to maximize the minimum detectability index for many locations sampled throughout the volume. To reduce the dimensionality, FFM patterns were represented using wavelet bases, the coefficients of which were optimized using the covariance matrix adaptation evolutionary strategy (CMA-ES) algorithm. The optimization was performed for a mid-frequency discrimination task involving a cluster of micro-calcifications in an abdomen phantom. The task-driven design yielded FFM patterns that were significantly different from traditional strategies proposed for FBP reconstruction. In addition to a higher minimum d' consistent with the objective function, the task-driven approach also improved d' to a greater extent over a larger area of the phantom. Results from this work suggests that FFM strategies suitable for FBP reconstruction need to be reevaluated in the context of MBIR and that a task-driven imaging framework provides a promising approach for such optimization.

  12. 'Orbital volume restoration rate after orbital fracture'; a CT-based orbital volume measurement for evaluation of orbital wall reconstructive effect.

    PubMed

    Wi, J M; Sung, K H; Chi, M

    2017-01-13

    PurposeTo evaluate the effect of orbital reconstruction and factors related to the effect of orbital reconstruction by assessing of orbital volume using orbital computed tomography (CT) in cases of orbital wall fracture.MethodsIn this retrospective study, 68 patients with isolated blowout fractures were evaluated. The volumes of orbits and herniated orbital tissues were determined by CT scans using a three-dimensional reconstruction technique (the Eclipse Treatment Planning System). Orbital CT was performed preoperatively, immediately after surgery, and at final follow ups (minimum of 6 months). We evaluated the reconstructive effect of surgery making a new formula, 'orbital volume reconstruction rate' from orbital volume differences between fractured and contralateral orbits before surgery, immediately after surgery, and at final follow up.ResultsMean volume of fractured orbits before surgery was 23.01±2.60 cm(3) and that of contralateral orbits was 21.31±2.50 cm(3) (P=0.005). Mean volume of the fractured orbits immediately after surgery was 21.29±2.42 cm(3), and that of the contralateral orbits was 21.33±2.52 cm(3) (P=0.921). Mean volume of fractured orbits at final follow up was 21.50±2.44 cm(3), and that of contralateral orbits was 21.32±2.50 cm(3) (P=0.668). The mean orbital volume reconstruction rate was 100.47% immediately after surgery and 99.17% at final follow up. No significant difference in orbital volume reconstruction rate was observed with respect to fracture site or orbital implant type. Patients that underwent operation within 14 days of trauma had a better reconstruction rate at final follow up than patients who underwent operation over 14 days after trauma (P=0.039).ConclusionComputer-based measurements of orbital fracture volume can be used to evaluate the reconstructive effect of orbital implants and provide useful quantitative information. Significant reduction of orbital volume is observed immediately after orbital wall

  13. Task-driven optimization of CT tube current modulation and regularization in model-based iterative reconstruction.

    PubMed

    Gang, Grace Jianan; Siewerdsen, Jeffrey; Stayman, Joseph

    2017-03-31

    Tube current modulation (TCM) is routinely adopted on diagnostic CT scanners for dose reduction. Conventional TCM strategies are generally designed for filtered-backprojection (FBP) reconstruction to satisfy simple image quality requirements based on noise. This work investigates TCM designs for model-based iterative reconstruction (MBIR) to achieve optimal imaging performance as determined by a task-based image quality metric. Additionally, regularization is an important aspect of MBIR that is jointly optimized with TCM, and includes both the regularization strength that controls overall smoothness as well as directional weights that permits control of the isotropy/anisotropy of the local noise and resolution properties. Initial investigations focus on a known imaging task at a single location in the image volume. The framework adopts Fourier and analytical approximations for fast estimation of the local noise power spectrum (NPS) and modulation transfer function (MTF) - each carrying dependencies on TCM and regularization. For the single location optimization, the local detectability index (d') of the specific task was directly adopted as the objective function. A covariance matrix adaptation evolution strategy (CMA-ES) algorithm was employed to identify the optimal combination of imaging parameters. Evaluations of both conventional and task-driven approaches were performed in an abdomen phantom for a mid-frequency discrimination task in the kidney. Among the conventional strategies, the TCM pattern optimal for FBP using a minimum variance criterion yielded worse task-based performance compared to an unmodulated strategy when applied to MBIR. Moreover, task-driven TCM designs for MBIR were found to have the opposite behavior from conventional designs for FBP, with greater fluence assigned to the less attenuating views of the abdomen and less fluence to the more attenuating lateral views. Such TCM patterns exaggerate the intrinsic anisotropy of the MTF and NPS as

  14. Analysis of bite marks in foodstuffs by computer tomography (cone beam CT)--3D reconstruction.

    PubMed

    Marques, Jeidson; Musse, Jamilly; Caetano, Catarina; Corte-Real, Francisco; Corte-Real, Ana Teresa

    2013-12-01

    The use of three-dimensional (3D) analysis of forensic evidence is highlighted in comparison with traditional methods. This three-dimensional analysis is based on the registration of the surface from a bitten object. The authors propose to use Cone Beam Computed Tomography (CBCT), which is used in dental practice, in order to study the surface and interior of bitten objects and dental casts of suspects. In this study, CBCT is applied to the analysis of bite marks in foodstuffs, which may be found in a forensic case scenario. 6 different types of foodstuffs were used: chocolate, cheese, apple, chewing gum, pizza and tart (flaky pastry and custard). The food was bitten into and dental casts of the possible suspects were made. The dental casts and bitten objects were registered using an x-ray source and the CBCT equipment iCAT® (Pennsylvania, EUA). The software InVivo5® (Anatomage Inc, EUA) was used to visualize and analyze the tomographic slices and 3D reconstructions of the objects. For each material an estimate of its density was assessed by two methods: HU values and specific gravity. All the used materials were successfully reconstructed as good quality 3D images. The relative densities of the materials in study were compared. Amongst the foodstuffs, the chocolate had the highest density (median value 100.5 HU and 1,36 g/cm(3)), while the pizza showed to have the lowest (median value -775 HU and 0,39 g/cm(3)), on both scales. Through tomographic slices and three-dimensional reconstructions it was possible to perform the metric analysis of the bite marks in all the foodstuffs, except for the pizza. These measurements could also be obtained from the dental casts. The depth of the bite mark was also successfully determined in all the foodstuffs except for the pizza. Cone Beam Computed Tomography has the potential to become an important tool for forensic sciences, namely for the registration and analysis of bite marks in foodstuffs that may be found in a crime

  15. SU-F-207-02: Use of Postmortem Subjects for Subjective Image Quality Assessment in Abdominal CT Protocols with Iterative Reconstruction

    SciTech Connect

    Mench, A; Lipnharski, I; Carranza, C; Lamoureux, R; Smajdor, L; Cormack, B; Mohammed, T; Rill, L; Arreola, M; Sinclair, L

    2015-06-15

    Purpose: New radiation dose reduction technologies are emerging constantly in the medical imaging field. The latest of these technologies, iterative reconstruction (IR) in CT, presents the ability to reduce dose significantly and hence provides great opportunity for CT protocol optimization. However, without effective analysis of image quality, the reduction in radiation exposure becomes irrelevant. This work explores the use of postmortem subjects as an image quality assessment medium for protocol optimizations in abdominal CT. Methods: Three female postmortem subjects were scanned using the Abdomen-Pelvis (AP) protocol at reduced minimum tube current and target noise index (SD) settings of 12.5, 17.5, 20.0, and 25.0. Images were reconstructed using two strengths of iterative reconstruction. Radiologists and radiology residents from several subspecialties were asked to evaluate 8 AP image sets including the current facility default scan protocol and 7 scans with the parameters varied as listed above. Images were viewed in the soft tissue window and scored on a 3-point scale as acceptable, borderline acceptable, and unacceptable for diagnosis. The facility default AP scan was identified to the reviewer while the 7 remaining AP scans were randomized and de-identified of acquisition and reconstruction details. The observers were also asked to comment on the subjective image quality criteria they used for scoring images. This included visibility of specific anatomical structures and tissue textures. Results: Radiologists scored images as acceptable or borderline acceptable for target noise index settings of up to 20. Due to the postmortem subjects’ close representation of living human anatomy, readers were able to evaluate images as they would those of actual patients. Conclusion: Postmortem subjects have already been proven useful for direct CT organ dose measurements. This work illustrates the validity of their use for the crucial evaluation of image quality

  16. Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction

    PubMed Central

    Yu, Lifeng; Li, Zhoubo; Manduca, Armando; Blezek, Daniel J.; Hough, David M.; Venkatesh, Sudhakar K.; Brickner, Gregory C.; Cernigliaro, Joseph C.; Hara, Amy K.; Fidler, Jeff L.; Lake, David S.; Shiung, Maria; Lewis, David; Leng, Shuai; Augustine, Kurt E.; Carter, Rickey E.; Holmes, David R.; McCollough, Cynthia H.

    2015-01-01

    Purpose To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). Materials and Methods This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per–malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than −0.10. Results Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: −0.041 [95% CI: −0.090, 0.009] and −0.003 [95% CI: −0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: −0.077, 0.106]), whereas lower-dose FBP images were not (difference −0.049 [95% CI:

  17. Cardiac image reconstruction on a 16-slice CT scanner using a retrospectively ECG-gated multicycle 3D back-projection algorithm

    NASA Astrophysics Data System (ADS)

    Shechter, Gilad; Naveh, Galit; Altman, Ami; Proksa, Roland M.; Grass, Michael

    2003-05-01

    Fast 16-slice spiral CT delivers superior cardiac visualization in comparison to older generation 2- to 8-slice scanners due to the combination of high temporal resolution along with isotropic spatial resolution and large coverage. The large beam opening of such scanners necessitates the use of adequate algorithms to avoid cone beam artifacts. We have developed a multi-cycle phase selective 3D back projection reconstruction algorithm that provides excellent temporal and spatial resolution for 16-slice CT cardiac images free of cone beam artifacts.

  18. SU-D-12A-06: A Comprehensive Parameter Analysis for Low Dose Cone-Beam CT Reconstruction

    SciTech Connect

    Lu, W; Yan, H; Gu, X; Jiang, S; Jia, X; Bai, T; Zhou, L

    2014-06-01

    Purpose: There is always a parameter in compressive sensing based iterative reconstruction (IR) methods low dose cone-beam CT (CBCT), which controls the weight of regularization relative to data fidelity. A clear understanding of the relationship between image quality and parameter values is important. The purpose of this study is to investigate this subject based on experimental data and a representative advanced IR algorithm using Tight-frame (TF) regularization. Methods: Three data sets of a Catphan phantom acquired at low, regular and high dose levels are used. For each tests, 90 projections covering a 200-degree scan range are used for reconstruction. Three different regions-of-interest (ROIs) of different contrasts are used to calculate contrast-to-noise ratios (CNR) for contrast evaluation. A single point structure is used to measure modulation transfer function (MTF) for spatial-resolution evaluation. Finally, we analyze CNRs and MTFs to study the relationship between image quality and parameter selections. Results: It was found that: 1) there is no universal optimal parameter. The optimal parameter value depends on specific task and dose level. 2) There is a clear trade-off between CNR and resolution. The parameter for the best CNR is always smaller than that for the best resolution. 3) Optimal parameters are also dose-specific. Data acquired under a high dose protocol require less regularization, yielding smaller optimal parameter values. 4) Comparing with conventional FDK images, TF-based CBCT images are better under a certain optimally selected parameters. The advantages are more obvious for low dose data. Conclusion: We have investigated the relationship between image quality and parameter values in the TF-based IR algorithm. Preliminary results indicate optimal parameters are specific to both the task types and dose levels, providing guidance for selecting parameters in advanced IR algorithms. This work is supported in part by NIH (1R01CA154747-01)

  19. Activity concentration measurements using a conjugate gradient (Siemens xSPECT) reconstruction algorithm in SPECT/CT.

    PubMed

    Armstrong, Ian S; Hoffmann, Sandra A

    2016-11-01

    The interest in quantitative single photon emission computer tomography (SPECT) shows potential in a number of clinical applications and now several vendors are providing software and hardware solutions to allow 'SUV-SPECT' to mirror metrics used in PET imaging. This brief technical report assesses the accuracy of activity concentration measurements using a new algorithm 'xSPECT' from Siemens Healthcare. SPECT/CT data were acquired from a uniform cylinder with 5, 10, 15 and 20 s/projection and NEMA image quality phantom with 25 s/projection. The NEMA phantom had hot spheres filled with an 8 : 1 activity concentration relative to the background compartment. Reconstructions were performed using parameters defined by manufacturer presets available with the algorithm. The accuracy of activity concentration measurements was assessed. A dose calibrator-camera cross-calibration factor (CCF) was derived from the uniform phantom data. In uniform phantom images, a positive bias was observed, ranging from ∼6% in the lower count images to ∼4% in the higher-count images. On the basis of the higher-count data, a CCF of 0.96 was derived. As expected, considerable negative bias was measured in the NEMA spheres using region mean values whereas positive bias was measured in the four largest NEMA spheres. Nonmonotonically increasing recovery curves for the hot spheres suggested the presence of Gibbs edge enhancement from resolution modelling. Sufficiently accurate activity concentration measurements can easily be measured on images reconstructed with the xSPECT algorithm without a CCF. However, the use of a CCF is likely to improve accuracy further. A manual conversion of voxel values into SUV should be possible, provided that the patient weight, injected activity and time between injection and imaging are all known accurately.

  20. A high-resolution photon-counting breast CT system with tensor-framelet based iterative image reconstruction for radiation dose reduction

    PubMed Central

    Ding, Huanjun; Gao, Hao; Zhao, Bo; Cho, Hyo-Min; Molloi, Sabee

    2016-01-01

    Both computer simulations and experimental phantom studies were carried out to investigate the radiation dose reduction with tensor framelet based iterative image reconstruction (TFIR) for a dedicated high-resolution spectral breast computed tomography (CT) based on a silicon strip photon-counting detector. The simulation was performed with a 10 cm-diameter water phantom including three contrast materials (polyethylene, 8 mg/ml iodine and B-100 bone-equivalent plastic). In the experimental study, the data were acquired with a 1.3 cm-diameter polymethylmethacrylate (PMMA) phantom containing iodine in three concentrations (8, 16 and 32 mg/ml) at various radiation doses (1.2, 2.4 and 3.6 mGy) and then CT images were reconstructed using filtered-back-projection (FBP) technique and TFIR technique, respectively. The image quality between these two techniques was evaluated by the quantitative analysis on contrast-to-noise ratio (CNR) and spatial resolution that was evaluated using the tasked-based modulation transfer function (MTF). Both simulation and experimental results indicated that the task-based MTF obtained from TFIR reconstruction with one-third of the radiation dose was comparable to that from FBP reconstruction for low contrast target. For high contrast target, TFIR was substantially superior to FBP reconstruction in term of spatial resolution. In addition, TFIR was able to achieve a factor of 1.6 to 1.8 increase in CNR depending on the target contrast level. This study demonstrates that TFIR can reduce the required radiation dose by a factor of two-third for a CT image reconstruction compared to FBP technique. It achieves much better CNR and spatial resolution for high contrast target in addition to retaining similar spatial resolution for low contrast target. This TFIR technique has been implemented with a graphic processing unit (GPU) system and it takes approximately 10 seconds to reconstruct a single-slice CT image, which can be potentially used in a

  1. 3-Dimensional Topographic Models for the Classroom

    NASA Technical Reports Server (NTRS)

    Keller, J. W.; Roark, J. H.; Sakimoto, S. E. H.; Stockman, S.; Frey, H. V.

    2003-01-01

    We have recently undertaken a program to develop educational tools using 3-dimensional solid models of digital elevation data acquired by the Mars Orbital Laser Altimeter (MOLA) for Mars as well as a variety of sources for elevation data of the Earth. This work is made possible by the use of rapid prototyping technology to construct solid 3-Dimensional models of science data. We recently acquired rapid prototyping machine that builds 3-dimensional models in extruded plastic. While the machine was acquired to assist in the design and development of scientific instruments and hardware, it is also fully capable of producing models of spacecraft remote sensing data. We have demonstrated this by using Mars Orbiter Laser Altimeter (MOLA) topographic data and Earth based topographic data to produce extruded plastic topographic models which are visually appealing and instantly engage those who handle them.

  2. Improving the quality of reconstructed X-ray CT images of polymer gel dosimeters: zero-scan coupled with adaptive mean filtering.

    PubMed

    Kakakhel, M B; Jirasek, A; Johnston, H; Kairn, T; Trapp, J V

    2017-03-01

    This study evaluated the feasibility of combining the 'zero-scan' (ZS) X-ray computed tomography (CT) based polymer gel dosimeter (PGD) readout with adaptive mean (AM) filtering for improving the signal to noise ratio (SNR), and to compare these results with available average scan (AS) X-ray CT readout techniques. NIPAM PGD were manufactured, irradiated with 6 MV photons, CT imaged and processed in Matlab. AM filter for two iterations, with 3 × 3 and 5 × 5 pixels (kernel size), was used in two scenarios (a) the CT images were subjected to AM filtering (pre-processing) and these were further employed to generate AS and ZS gel images, and (b) the AS and ZS images were first reconstructed from the CT images and then AM filtering was carried out (post-processing). SNR was computed in an ROI of 30 × 30 for different pre and post processing cases. Results showed that the ZS technique combined with AM filtering resulted in improved SNR. Using the previously-recommended 25 images for reconstruction the ZS pre-processed protocol can give an increase of 44% and 80% in SNR for 3 × 3 and 5 × 5 kernel sizes respectively. However, post processing using both techniques and filter sizes introduced blur and a reduction in the spatial resolution. Based on this work, it is possible to recommend that the ZS method may be combined with pre-processed AM filtering using appropriate kernel size, to produce a large increase in the SNR of the reconstructed PGD images.

  3. Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure

    SciTech Connect

    Maier, Joscha; Sawall, Stefan; Kachelrieß, Marc

    2014-05-15

    Purpose: Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Methods: Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Results: Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the

  4. SU-E-T-143: Effect of X-Ray and Cone Beam CT Reconstruction Parameters On Estimation of Bone Volume of Mice Used in Aging Research

    SciTech Connect

    Russ, M; Pang, M; Troen, B; Rudin, S; Ionita, C

    2014-06-01

    Purpose: To investigate the variations in bone volume calculations in mice involved in aging research when changing cone beam micro-CT x-ray and reconstruction parameters. Methods: Mouse spines were placed on an indexed turn table that rotated 0.5° per projection and imaged by a self-built micro CT machine containing a CCD-based high-resolution x-ray detector. After the full 360° rotation data set of object images was obtained, a standard filtered back-projection cone beam reconstruction was performed. Four different kVp's between 40–70 kVp in 10kVp increments were selected. For each kVp two mAs settings were used. Each acquisition was reconstructed using two voxel sizes (12 and 25μm) and two step angles, 0.5° and 1°, respectively. A LabView program was written to determine the total bone volume contained in the mouse's total spine volume (bone plus gaps) as a measure of spine health. First, the user selected the desired 512×512 reconstruction to view the whole spine volume which was then used to select a gray-level threshold that allowed for viewing of the bone structure, then another threshold to include gaps. The program returned bone volume, bone × gap volume, and their ratio, BVF. Results: The calculated bone volume fractions were compared as a function of tube potential. Cases with 25μm slice thickness showed trials with lower kVp's had greater image contrast, which resulted in higher calculated bone volume fractions. Cases with 12μm reconstructed slice thickness were significantly noisier, and showed no clear maximum BVF. Conclusion: Using the projection images and reconstructions acquired from the micro CT, it can be shown that the micro-CT x-ray and reconstruction parameters significantly affect the total bone volume calculations. When comparing mice cohorts treated with different therapies researchers need to be aware of such details and use volumes which were acquired and processed in identical conditions.

  5. A phantom-based JAFROC observer study of two CT reconstruction methods: the search for optimisation of lesion detection and effective dose

    NASA Astrophysics Data System (ADS)

    Thompson, John D.; Chakraborty, Dev P.; Szczepura, Katy; Vamvakas, Ioannis; Tootell, Andrew; Manning, David J.; Hogg, Peter

    2015-03-01

    Purpose: To investigate the dose saving potential of iterative reconstruction (IR) in a computed tomography (CT) examination of the thorax. Materials and Methods: An anthropomorphic chest phantom containing various configurations of simulated lesions (5, 8, 10 and 12mm; +100, -630 and -800 Hounsfield Units, HU) was imaged on a modern CT system over a tube current range (20, 40, 60 and 80mA). Images were reconstructed with (IR) and filtered back projection (FBP). An ATOM 701D (CIRS, Norfolk, VA) dosimetry phantom was used to measure organ dose. Effective dose was calculated. Eleven observers (15.11+/-8.75 years of experience) completed a free response study, localizing lesions in 544 single CT image slices. A modified jackknife alternative free-response receiver operating characteristic (JAFROC) analysis was completed to look for a significant effect of two factors: reconstruction method and tube current. Alpha was set at 0.05 to control the Type I error in this study. Results: For modified JAFROC analysis of reconstruction method there was no statistically significant difference in lesion detection performance between FBP and IR when figures-of-merit were averaged over tube current (F(1,10)=0.08, p = 0.789). For tube current analysis, significant differences were revealed between multiple pairs of tube current settings (F(3,10) = 16.96, p<0.001) when averaged over image reconstruction method. Conclusion: The free-response study suggests that lesion detection can be optimized at 40mA in this phantom model, a measured effective dose of 0.97mSv. In high-contrast regions the diagnostic value of IR, compared to FBP, is less clear.

  6. Dual-energy cone-beam CT with a flat-panel detector: Effect of reconstruction algorithm on material classification

    SciTech Connect

    Zbijewski, W. Gang, G. J.; Xu, J.; Wang, A. S.; Stayman, J. W.; Taguchi, K.; Carrino, J. A.; Siewerdsen, J. H.

    2014-02-15

    Purpose: Cone-beam CT (CBCT) with a flat-panel detector (FPD) is finding application in areas such as breast and musculoskeletal imaging, where dual-energy (DE) capabilities offer potential benefit. The authors investigate the accuracy of material classification in DE CBCT using filtered backprojection (FBP) and penalized likelihood (PL) reconstruction and optimize contrast-enhanced DE CBCT of the joints as a function of dose, material concentration, and detail size. Methods: Phantoms consisting of a 15 cm diameter water cylinder with solid calcium inserts (50–200 mg/ml, 3–28.4 mm diameter) and solid iodine inserts (2–10 mg/ml, 3–28.4 mm diameter), as well as a cadaveric knee with intra-articular injection of iodine were imaged on a CBCT bench with a Varian 4343 FPD. The low energy (LE) beam was 70 kVp (+0.2 mm Cu), and the high energy (HE) beam was 120 kVp (+0.2 mm Cu, +0.5 mm Ag). Total dose (LE+HE) was varied from 3.1 to 15.6 mGy with equal dose allocation. Image-based DE classification involved a nearest distance classifier in the space of LE versus HE attenuation values. Recognizing the differences in noise between LE and HE beams, the LE and HE data were differentially filtered (in FBP) or regularized (in PL). Both a quadratic (PLQ) and a total-variation penalty (PLTV) were investigated for PL. The performance of DE CBCT material discrimination was quantified in terms of voxelwise specificity, sensitivity, and accuracy. Results: Noise in the HE image was primarily responsible for classification errors within the contrast inserts, whereas noise in the LE image mainly influenced classification in the surrounding water. For inserts of diameter 28.4 mm, DE CBCT reconstructions were optimized to maximize the total combined accuracy across the range of calcium and iodine concentrations, yielding values of ∼88% for FBP and PLQ, and ∼95% for PLTV at 3.1 mGy total dose, increasing to ∼95% for FBP and PLQ, and ∼98% for PLTV at 15.6 mGy total dose. For a

  7. 3-dimensional imaging at nanometer resolutions

    DOEpatents

    Werner, James H.; Goodwin, Peter M.; Shreve, Andrew P.

    2010-03-09

    An apparatus and method for enabling precise, 3-dimensional, photoactivation localization microscopy (PALM) using selective, two-photon activation of fluorophores in a single z-slice of a sample in cooperation with time-gated imaging for reducing the background radiation from other image planes to levels suitable for single-molecule detection and spatial location, are described.

  8. Nonlinear statistical reconstruction for flat-panel cone-beam CT with blur and correlated noise models

    NASA Astrophysics Data System (ADS)

    Tilley, Steven; Siewerdsen, Jeffrey H.; Zbijewski, Wojciech; Stayman, J. Webster

    2016-03-01

    Flat-panel cone-beam CT (FP-CBCT) is a promising imaging modality, partly due to its potential for high spatial resolution reconstructions in relatively compact scanners. Despite this potential, FP-CBCT can face difficulty resolving important fine scale structures (e.g, trabecular details in dedicated extremities scanners and microcalcifications in dedicated CBCT mammography). Model-based methods offer one opportunity to improve high-resolution performance without any hardware changes. Previous work, based on a linearized forward model, demonstrated improved performance when both system blur and spatial correlations characteristics of FP-CBCT systems are modeled. Unfortunately, the linearized model relies on a staged processing approach that complicates tuning parameter selection and can limit the finest achievable spatial resolution. In this work, we present an alternative scheme that leverages a full nonlinear forward model with both system blur and spatially correlated noise. A likelihood-based objective function is derived from this forward model and we derive an iterative optimization algorithm for its solution. The proposed approach is evaluated in simulation studies using a digital extremities phantom and resolution-noise trade-offs are quantitatively evaluated. The correlated nonlinear model outperformed both the uncorrelated nonlinear model and the staged linearized technique with up to a 86% reduction in variance at matched spatial resolution. Additionally, the nonlinear models could achieve finer spatial resolution (correlated: 0.10 mm, uncorrelated: 0.11 mm) than the linear correlated model (0.15 mm), and traditional FDK (0.40 mm). This suggests the proposed nonlinear approach may be an important tool in improving performance for high-resolution clinical applications.

  9. Nonlinear Statistical Reconstruction for Flat-Panel Cone-Beam CT with Blur and Correlated Noise Models

    PubMed Central

    Tilley, Steven; Siewerdsen, Jeffrey H.; Zbijewski, Wojciech; Stayman, J. Webster

    2016-01-01

    Flat-panel cone-beam CT (FP-CBCT) is a promising imaging modality, partly due to its potential for high spatial resolution reconstructions in relatively compact scanners. Despite this potential, FP-CBCT can face difficulty resolving important fine scale structures (e.g, trabecular details in dedicated extremities scanners and microcalcifications in dedicated CBCT mammography). Model-based methods offer one opportunity to improve high-resolution performance without any hardware changes. Previous work, based on a linearized forward model, demonstrated improved performance when both system blur and spatial correlations characteristics of FP-CBCT systems are modeled. Unfortunately, the linearized model relies on a staged processing approach that complicates tuning parameter selection and can limit the finest achievable spatial resolution. In this work, we present an alternative scheme that leverages a full nonlinear forward model with both system blur and spatially correlated noise. A likelihood-based objective function is derived from this forward model and we derive an iterative optimization algorithm for its solution. The proposed approach is evaluated in simulation studies using a digital extremities phantom and resolution-noise trade-offs are quantitatively evaluated. The correlated nonlinear model outperformed both the uncorrelated nonlinear model and the staged linearized technique with up to a 86% reduction in variance at matched spatial resolution. Additionally, the nonlinear models could achieve finer spatial resolution (correlated: 0.10 mm, uncorrelated: 0.11 mm) than the linear correlated model (0.15 mm), and traditional FDK (0.40 mm). This suggests the proposed nonlinear approach may be an important tool in improving performance for high-resolution clinical applications. PMID:27110051

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

    SciTech Connect

    Gao, Y; Thomas, D; Low, D; Gao, H

    2014-06-01

    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

  11. SU-E-T-189: First Experimental Verification of the Accuracy of Absolute Dose Reconstruction From PET-CT Imaging of Yttrium 90 Microspheres

    SciTech Connect

    Veltchev, I; Fourkal, E; Doss, M; Ma, C; Meyer, J; Yu, M; Horwitz, E

    2014-06-01

    Purpose: In the past few years there have been numerous proposals for 3D dose reconstruction from the PET-CT imaging of patients undergoing radioembolization treatment of the liver with yttrium-90 microspheres. One of the most promising techniques uses convolution of the measured PET activity distribution with a pre-calculated Monte Carlo dose deposition kernel. The goal of the present study is to experimentally verify the accuracy of this method and to analyze the significance of various error sources. Methods: Optically stimulated luminescence detectors (OSLD) were used (NanoDot, Landauer) in this experiment. Two detectors were mounted on the central axis of a cylinder filled with water solution of yttrium-90 chloride. The total initial activity was 90mCi. The cylinder was inserted in a larger water phantom and scanned on a Siemens Biograph 16 Truepoint PET-CT scanner. Scans were performed daily over a period of 20 days to build a calibration curve for the measured absolute activity spanning 7 yttrium-90 half-lives. The OSLDs were mounted in the phantom for a predetermined period of time in order to record 2Gy dose. The measured dose was then compared to the dose reconstructed from the activity density at the location of each dosimeter. Results: Thorough error analysis of the dose reconstruction algorithm takes into account the uncertainties in the absolute PET activity, branching ratios, and nonlinearity of the calibration curve. The measured dose for 105-minute exposure on day 10 of the experiment was 219(11)cGy, while the reconstructed dose at the location of the detector was 215(47)cGy. Conclusion: We present the first experimental verification of the accuracy of the convolution algorithm for absolute dose reconstruction of yttrium-90 microspheres. The excellent agreement between the measured and calculated point doses will encourage the broad clinical adoption of the convolution-based dose reconstruction algorithm, making future quantitative dose

  12. Comparison between human and model observer performance in low-contrast detection tasks in CT images: application to images reconstructed with filtered back projection and iterative algorithms

    PubMed Central

    Calzado, A; Geleijns, J; Joemai, R M S; Veldkamp, W J H

    2014-01-01

    Objective: To compare low-contrast detectability (LCDet) performance between a model [non–pre-whitening matched filter with an eye filter (NPWE)] and human observers in CT images reconstructed with filtered back projection (FBP) and iterative [adaptive iterative dose reduction three-dimensional (AIDR 3D; Toshiba Medical Systems, Zoetermeer, Netherlands)] algorithms. Methods: Images of the Catphan® phantom (Phantom Laboratories, New York, NY) were acquired with Aquilion ONE™ 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan) at five tube current levels (20–500 mA range) and reconstructed with FBP and AIDR 3D. Samples containing either low-contrast objects (diameters, 2–15 mm) or background were extracted and analysed by the NPWE model and four human observers in a two-alternative forced choice detection task study. Proportion correct (PC) values were obtained for each analysed object and used to compare human and model observer performances. An efficiency factor (η) was calculated to normalize NPWE to human results. Results: Human and NPWE model PC values (normalized by the efficiency, η = 0.44) were highly correlated for the whole dose range. The Pearson's product-moment correlation coefficients (95% confidence interval) between human and NPWE were 0.984 (0.972–0.991) for AIDR 3D and 0.984 (0.971–0.991) for FBP, respectively. Bland–Altman plots based on PC results showed excellent agreement between human and NPWE [mean absolute difference 0.5 ± 0.4%; range of differences (−4.7%, 5.6%)]. Conclusion: The NPWE model observer can predict human performance in LCDet tasks in phantom CT images reconstructed with FBP and AIDR 3D algorithms at different dose levels. Advances in knowledge: Quantitative assessment of LCDet in CT can accurately be performed using software based on a model observer. PMID:24837275

  13. Low-dose dynamic myocardial perfusion CT image reconstruction using pre-contrast normal-dose CT scan induced structure tensor total variation regularization

    NASA Astrophysics Data System (ADS)

    Gong, Changfei; Han, Ce; Gan, Guanghui; Deng, Zhenxiang; Zhou, Yongqiang; Yi, Jinling; Zheng, Xiaomin; Xie, Congying; Jin, Xiance

    2017-04-01

    Dynamic myocardial perfusion CT (DMP-CT) imaging provides quantitative functional information for diagnosis and risk stratification of coronary artery disease by calculating myocardial perfusion hemodynamic parameter (MPHP) maps. However, the level of radiation delivered by dynamic sequential scan protocol can be potentially high. The purpose of this work is to develop a pre-contrast normal-dose scan induced structure tensor total variation regularization based on the penalized weighted least-squares (PWLS) criteria to improve the image quality of DMP-CT with a low-mAs CT acquisition. For simplicity, the present approach was termed as ‘PWLS-ndiSTV’. Specifically, the ndiSTV regularization takes into account the spatial-temporal structure information of DMP-CT data and further exploits the higher order derivatives of the objective images to enhance denoising performance. Subsequently, an effective optimization algorithm based on the split-Bregman approach was adopted to minimize the associative objective function. Evaluations with modified dynamic XCAT phantom and preclinical porcine datasets have demonstrated that the proposed PWLS-ndiSTV approach can achieve promising gains over other existing approaches in terms of noise-induced artifacts mitigation, edge details preservation, and accurate MPHP maps calculation.

  14. Preoperative 3-dimensional Magnetic Resonance Imaging of Uterine Myoma and Endometrium Before Myomectomy.

    PubMed

    Kim, Young Jae; Kim, Kwang Gi; Lee, Sa Ra; Lee, Seung Hyun; Kang, Byung Chul

    2017-02-01

    Uterine myomas are the most common gynecologic benign tumor affecting women of childbearing age, and myomectomy is the main surgical option to preserve the uterus and fertility. During myomectomy for women with multiple myomas, it is advisable to identify and remove as many as possible to decrease the risk of future myomectomies. With deficient preoperative imaging, gynecologists are challenged to identify the location and size of myomas and the endometrium, which, in turn, can lead to uterine rupture during future pregnancies. Current conventional 2-dimensional imaging has limitations in identifying precise locations of multiple myomas and the endometrium. In our experience, we preferred to use 3-dimensional imaging to delineate the myomas, endometrium, or blood vessels, which we were able to successfully reconstruct by using the following imaging method. To achieve 3-dimensional imaging, we matched T2 turbo spin echo images to detect uterine myomas and endometria with T1 high-resolution isotropic volume excitation-post images used to detect blood vessels by using an algorithm based on the 3-dimensional region growing method. Then, we produced images of the uterine myomas, endometria, and blood vessels using a 3-dimensional surface rendering method and successfully reconstructed selective 3-dimensional imaging for uterine myomas, endometria, and adjacent blood vessels. A Web-based survey was sent to 66 gynecologists concerning imaging techniques used before myomectomy. Twenty-eight of 36 responding gynecologists answered that the 3-dimensional image produced in the current study is preferred to conventional 2-dimensional magnetic resonance imaging in identifying precise locations of uterine myomas and endometria. The proposed 3-dimensional magnetic resonance imaging method successfully reconstructed uterine myomas, endometria, and adjacent vessels. We propose that this will be a helpful adjunct to uterine myomectomy as a preoperative imaging technique in future

  15. SU-F-18C-13: Low-Dose X-Ray CT Reconstruction Using a Hybrid First-Order Method

    SciTech Connect

    Liu, L; Lin, W; Jin, M

    2014-06-15

    Purpose: To develop a novel reconstruction method for X-ray CT that can lead to accurate reconstruction at significantly reduced dose levels combining low X-ray incident intensity and few views of projection data. Methods: The noise nature of the projection data at low X-ray incident intensity was modeled and accounted by the weighted least-squares (WLS) criterion. The total variation (TV) penalty was used to mitigate artifacts caused by few views of data. The first order primal-dual (FOPD) algorithm was used to minimize TV in image domain, which avoided the difficulty of the non-smooth objective function. The TV penalized WLS reconstruction was achieved by alternated FOPD TV minimization and projection onto convex sets (POCS) for data fidelity constraints. The proposed FOPD-POCS method was evaluated using the FORBILD jaw phantom and the real cadaver head CT data. Results: The quantitative measures, root mean square error (RMSE) and contrast-to-noise ratio (CNR), demonstrate the superior denoising capability of WLS over LS-based TV iterative reconstruction. The improvement of RMSE (WLS vs. LS) is 15%∼21% and that of CNR is 17%∼72% when the incident counts per ray are ranged from 1×10{sup 5} to 1×10{sup 3}. In addition, the TV regularization can accurately reconstruct images from about 50 views of the jaw phantom. The FOPD-POCS reconstruction reveals more structural details and suffers fewer artifacts in both the phantom and real head images. The FOPD-POCS method also shows fast convergence at low X-ray incident intensity. Conclusion: The new hybrid FOPD-POCS method, based on TV penalized WLS, yields excellent image quality when the incident X-ray intensity is low and the projection views are limited. The reconstruction is computationally efficient since the FOPD minimization of TV is applied only in the image domain. The characteristics of FOPD-POCS can be exploited to significantly reduce radiation dose of X-ray CT without compromising accuracy for diagnosis

  16. SU-F-18C-02: Evaluations of the Noise Power Spectrum of a CT Iterative Reconstruction Technique for Radiation Therapy

    SciTech Connect

    Dolly, S; Chen, H; Anastasio, M; Mutic, S; Li, H

    2014-06-15

    Purpose: To quantitatively assess the noise power spectrum (NPS) of the new, commercially released CT iterative reconstruction technique, iDose{sup 4} from Philips, to compare it with filtered back-projection techniques (FBP), and to provide clinical practice suggestions for radiation therapy. Methods: A uniform phantom was CT imaged with 120kVp tube potential over a range of mAs (250-3333). The image sets were reconstructed using two reconstruction algorithms (FBP and iDose{sup 4} with noise reduction levels 1, 3, and 6) and three reconstruction filters (standard B, smooth A, and sharp C), after which NPS variations were analyzed and compared on region of interest (ROI) sizes (16×16 to 128×128 pixels), ROI radii (0–65 mm), reconstruction algorithms, reconstruction filters, and mAs. Results: The NPS magnitude and shape depended considerably on ROI size and location for both reconstruction algorithms. Regional noise variance became more stationary as ROI size decreased, minimizing NPS artifacts. The optimal 32×32-pixel ROI size balanced the trade-off between stationary noise and adequate sampling. NPS artifacts were greatest at the center of reconstruction space and decreased with increasing ROI distance from the center. The optimal ROI position was located near the phantom's radial midpoint (∼40mm). For sharper filters, the NPS magnitude and the maximum magnitude frequency increased. Higher dose scans yielded lower NPS magnitudes for both reconstruction algorithms and all filters. Compared to FBP, the iDose{sup 4} algorithm reduced the NPS magnitude while preferentially reducing noise at mid-range spatial frequencies, altering noise texture. This reduction was more significant with increasing iDose{sup 4} noise reduction level. Conclusion: Compared to pixel standard deviation, NPS has greater clinical potential for task-based image quality assessment, describing both the magnitude and spatial frequency characteristics of image noise. While iDose{sup 4

  17. MIRD Pamphlet No. 23: Quantitative SPECT for Patient-Specific 3-Dimensional Dosimetry in Internal Radionuclide Therapy

    PubMed Central

    Dewaraja, Yuni K.; Frey, Eric C.; Sgouros, George; Brill, A. Bertrand; Roberson, Peter; Zanzonico, Pat B.; Ljungberg, Michael

    2012-01-01

    In internal radionuclide therapy, a growing interest in voxel-level estimates of tissue-absorbed dose has been driven by the desire to report radiobiologic quantities that account for the biologic consequences of both spatial and temporal nonuniformities in these dose estimates. This report presents an overview of 3-dimensional SPECT methods and requirements for internal dosimetry at both regional and voxel levels. Combined SPECT/CT image-based methods are emphasized, because the CT-derived anatomic information allows one to address multiple technical factors that affect SPECT quantification while facilitating the patient-specific voxel-level dosimetry calculation itself. SPECT imaging and reconstruction techniques for quantification in radionuclide therapy are not necessarily the same as those designed to optimize diagnostic imaging quality. The current overview is intended as an introduction to an upcoming series of MIRD pamphlets with detailed radionuclide-specific recommendations intended to provide best-practice SPECT quantification–based guidance for radionuclide dosimetry. PMID:22743252

  18. Dose and Image Quality in Low-dose CT for Urinary Stone Disease: Added Value of Automatic Tube Current Modulation and Iterative Reconstruction Techniques.

    PubMed

    Soenen, Olivier; Balliauw, Christophe; Oyen, Raymond; Zanca, Federica

    2016-05-31

    The aim of this study was to compare dose and image quality (IQ) of a baseline low-dose computed tomography (CT) (fix mAs) vs. an ultra-low-dose CT (automatic tube current modulation, ATCM) in patients with suspected urinary stone disease and to assess the added value of iterative reconstruction. CT examination was performed on 193 patients (103 baseline low-dose, 90 ultra-low-dose). Filtered back projection (FBP) was used for both protocols, and Sinogram Affirmed Iterative Reconstruction (SAFIRE) was used for the ultra-low-dose protocol only. Dose and ureter stones information were collected for both protocols. Subjective IQ was assessed by two radiologists scoring noise, visibility of the ureter and overall IQ. Objective IQ (contrast-to-noise ratio, CNR) was assessed for the ultra-low-dose protocol only (FBP and SAFIRE). The ultra-low-dose protocol (ATCM) showed a 22% decrease in mean effective dose (p < 0.001) and improved visibility of the pelvic ureter (p = 0.02). CNR was higher for SAFIRE (p < 0.0001). SAFIRE improves the objective IQ, but not the subjective IQ for the chosen clinical task.

  19. SU-F-207-09: Evaluating the Dosimetric Accuracy of Extended Field-Of-View CT Reconstructions Using Clinical Data with Real Patient Geometries

    SciTech Connect

    Shugard, E; Cheung, J; Pouliot, J; Chen, J; Mistry, N

    2015-06-15

    Purpose: To determine the accuracy of dose calculations performed with CT images reconstructed using extended field of view (FOV) algorithms. Methods: In this study we selected 6 radiotherapy patients (3 head and neck & 3 chest/pelvis) whose body circumferences extended past the 50 cm scan FOV in the treatment planning CT. Images acquired on a Siemens Sensation Open scanner, were reconstructed using the standard FOV (sFOV) and two different extended FOV algorithms, eFOV and HDFOV. A physician and dosimetrist identified the radiation target, critical organs, and external patient contour. A benchmark CT was created for each patient, consisting of an average of the 3 CT reconstructions with a density override applied to regions containing truncation artifacts, and was used to create an optimal radiation treatment plan. The plan was copied onto each reconstruction without density override and dose was recalculated. Results: The native sFOV dose calculations had the largest deviation from the benchmark (0.4 – 6.0%). Both the HDFOV and eFOV calculations showed improvement over the sFOV. For patients with a smooth patient contour, the HDFOV calculation had the least deviation from the benchmark (0.1–0.5%) compared to eFOV (0.4–1.8%). In cases with large amounts of tissue and irregular skin folds, the eFOV deviated the least from the benchmark (0.2–0.6%) compared to HDFOV (1.3–1.8%). It was observed that the eFOV scan has large image artifact in air with an average HU of −600 compared to the ideal of −1000. In these cases, the artifact in air appears to attenuate the dose and compensate for the missing tissue density. The HDFOV demonstrated minimal artifact in air. Conclusion: Both eFOV and HDFOV provide improved dose calculation accuracy. The HDFOV reconstruction provides a clearer patient border than the eFOV allowing for well-defined density overrides to be applied with minimal air artifact. This research was supported by Siemens Medical Solutions.

  20. 3-dimensional fabrication of soft energy harvesters

    NASA Astrophysics Data System (ADS)

    McKay, Thomas; Walters, Peter; Rossiter, Jonathan; O'Brien, Benjamin; Anderson, Iain

    2013-04-01

    Dielectric elastomer generators (DEG) provide an opportunity to harvest energy from low frequency and aperiodic sources. Because DEG are soft, deformable, high energy density generators, they can be coupled to complex structures such as the human body to harvest excess mechanical energy. However, DEG are typically constrained by a rigid frame and manufactured in a simple planar structure. This planar arrangement is unlikely to be optimal for harvesting from compliant and/or complex structures. In this paper we present a soft generator which is fabricated into a 3 Dimensional geometry. This capability will enable the 3-dimensional structure of a dielectric elastomer to be customised to the energy source, allowing efficient and/or non-invasive coupling. This paper demonstrates our first 3 dimensional generator which includes a diaphragm with a soft elastomer frame. When the generator was connected to a self-priming circuit and cyclically inflated, energy was accumulated in the system, demonstrated by an increased voltage. Our 3D generator promises a bright future for dielectric elastomers that will be customised for integration with complex and soft structures. In addition to customisable geometries, the 3D printing process may lend itself to fabricating large arrays of small generator units and for fabricating truly soft generators with excellent impedance matching to biological tissue. Thus comfortable, wearable energy harvesters are one step closer to reality.

  1. Can use of adaptive statistical iterative reconstruction reduce radiation dose in unenhanced head CT? An analysis of qualitative and quantitative image quality

    PubMed Central

    Heggen, Kristin Livelten; Pedersen, Hans Kristian; Andersen, Hilde Kjernlie; Martinsen, Anne Catrine T

    2016-01-01

    Background Iterative reconstruction can reduce image noise and thereby facilitate dose reduction. Purpose To evaluate qualitative and quantitative image quality for full dose and dose reduced head computed tomography (CT) protocols reconstructed using filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR). Material and Methods Fourteen patients undergoing follow-up head CT were included. All patients underwent full dose (FD) exam and subsequent 15% dose reduced (DR) exam, reconstructed using FBP and 30% ASIR. Qualitative image quality was assessed using visual grading characteristics. Quantitative image quality was assessed using ROI measurements in cerebrospinal fluid (CSF), white matter, peripheral and central gray matter. Additionally, quantitative image quality was measured in Catphan and vendor’s water phantom. Results There was no significant difference in qualitative image quality between FD FBP and DR ASIR. Comparing same scan FBP versus ASIR, a noise reduction of 28.6% in CSF and between −3.7 and 3.5% in brain parenchyma was observed. Comparing FD FBP versus DR ASIR, a noise reduction of 25.7% in CSF, and −7.5 and 6.3% in brain parenchyma was observed. Image contrast increased in ASIR reconstructions. Contrast-to-noise ratio was improved in DR ASIR compared to FD FBP. In phantoms, noise reduction was in the range of 3 to 28% with image content. Conclusion There was no significant difference in qualitative image quality between full dose FBP and dose reduced ASIR. CNR improved in DR ASIR compared to FD FBP mostly due to increased contrast, not reduced noise. Therefore, we recommend using caution if reducing dose and applying ASIR to maintain image quality. PMID:27583169

  2. Hemodynamic Changes Caused by Flow Diverters in Rabbit Aneurysm Models: Comparison of Virtual and Realistic FD Deployments Based on Micro-CT Reconstruction.

    PubMed

    Xu, Jinyu; Deng, Benqiang; Fang, Yibin; Yu, Ying; Cheng, Jiyong; Wang, Shengzhang; Wang, Kuizhong; Liu, Jian-Min; Huang, Qinghai

    2013-01-01

    Adjusting hemodynamics via flow diverter (FD) implantation is emerging as a novel method of treating cerebral aneurysms. However, most previous FD-related hemodynamic studies were based on virtual FD deployment, which may produce different hemodynamic outcomes than realistic (in vivo) FD deployment. We compared hemodynamics between virtual FD and realistic FD deployments in rabbit aneurysm models using computational fluid dynamics (CFD) simulations. FDs were implanted for aneurysms in 14 rabbits. Vascular models based on rabbit-specific angiograms were reconstructed for CFD studies. Real FD configurations were reconstructed based on micro-CT scans after sacrifice, while virtual FD configurations were constructed with SolidWorks software. Hemodynamic parameters before and after FD deployment were analyzed. According to the metal coverage (MC) of implanted FDs calculated based on micro-CT reconstruction, 14 rabbits were divided into two groups (A, MC >35%; B, MC <35%). Normalized mean wall shear stress (WSS), relative residence time (RRT), inflow velocity, and inflow volume in Group A were significantly different (P<0.05) from virtual FD deployment, but pressure was not (P>0.05). The normalized mean WSS in Group A after realistic FD implantation was significantly lower than that of Group B. All parameters in Group B exhibited no significant difference between realistic and virtual FDs. This study confirmed MC-correlated differences in hemodynamic parameters between realistic and virtual FD deployment.

  3. SU-D-BRA-06: Dual-Energy Chest CT: The Effects of Virtual Monochromatic Reconstructions On Texture Analysis Features

    SciTech Connect

    Sorensen, J; Duran, C; Stingo, F; Wei, W; Rao, A; Zhang, L; Court, L; Erasmus, J; Godoy, M

    2015-06-15

    Purpose: To characterize the effect of virtual monochromatic reconstructions on several commonly used texture analysis features in DECT of the chest. Further, to assess the effect of monochromatic energy levels on the ability of these textural features to identify tissue types. Methods: 20 consecutive patients underwent chest CTs for evaluation of lung nodules using Siemens Somatom Definition Flash DECT. Virtual monochromatic images were constructed at 10keV intervals from 40–190keV. For each patient, an ROI delineated the lesion under investigation, and cylindrical ROI’s were placed within 5 different healthy tissues (blood, fat, muscle, lung, and liver). Several histogram- and Grey Level Cooccurrence Matrix (GLCM)-based texture features were then evaluated in each ROI at each energy level. As a means of validation, these feature values were then used in a random forest classifier to attempt to identify the tissue types present within each ROI. Their predictive accuracy at each energy level was recorded. Results: All textural features changed considerably with virtual monochromatic energy, particularly below 70keV. Most features exhibited a global minimum or maximum around 80keV, and while feature values changed with energy above this, patient ranking was generally unaffected. As expected, blood demonstrated the lowest inter-patient variability, for all features, while lung lesions (encompassing many different pathologies) exhibited the highest. The accuracy of these features in identifying tissues (76% accuracy) was highest at 80keV, but no clear relationship between energy and classification accuracy was found. Two common misclassifications (blood vs liver and muscle vs fat) accounted for the majority (24 of the 28) errors observed. Conclusion: All textural features were highly dependent on virtual monochromatic energy level, especially below 80keV, and were more stable above this energy. However, in a random forest model, these commonly used features were

  4. Three-dimensional visual truth of the normal airway tree for use as a quantitative comparison to micro-CT reconstructions

    NASA Astrophysics Data System (ADS)

    Thiesse, Jacqueline; Reinhardt, Joseph M.; de Ryk, Jessica; Namati, Eman; Leinen, Jessica; Recheis, Wolfgang A.; Hoffman, Eric A.; McLennan, Geoffrey

    2005-04-01

    Mouse models are important for pulmonary research to gain insight into structure and function in normal and diseased states, thereby extending knowledge of human disease conditions. The flexibility of human disease induction into mice, due to their similar genome, along with their short gestation cycle makes mouse models highly suitable as investigative tools. Advancements in non-invasive imaging technology, with the development of micro-computed tomography (μ-CT), have aided representation of disease states in these small pulmonary system models. The generation ofμCT 3D airway reconstructions has to date provided a means to examine structural changes associated with disease. The degree of accuracy ofμCT is uncertain. Consequently, the reliability of quantitative measurements is questionable. We have developed a method of sectioning and imaging the whole mouse lung using the Large Image Microscope Array (LIMA) as the gold standard for comparison. Fixed normal mouse lungs were embedded in agarose and 250μm sections of tissue were removed while the remaining tissue block was imaged with a stereomicroscope. A complete dataset of the mouse lung was acquired in this fashion. Following planar image registration, the airways were manually segmented using an in-house built software program PASS. Amira was then used render the 3D isosurface from the segmentations. The resulting 3D model of the normal mouse airway tree developed from pathology images was then quantitatively assessed and used as the standard to compare the accuracy of structural measurements obtained from μ-CT.

  5. Evaluation of hybrid SART  +  OS  +  TV iterative reconstruction algorithm for optical-CT gel dosimeter imaging

    NASA Astrophysics Data System (ADS)

    Du, Yi; Wang, Xiangang; Xiang, Xincheng; Wei, Zhouping

    2016-12-01

    Optical computed tomography (optical-CT) is a high-resolution, fast, and easily accessible readout modality for gel dosimeters. This paper evaluates a hybrid iterative image reconstruction algorithm for optical-CT gel dosimeter imaging, namely, the simultaneous algebraic reconstruction technique (SART) integrated with ordered subsets (OS) iteration and total variation (TV) minimization regularization. The mathematical theory and implementation workflow of the algorithm are detailed. Experiments on two different optical-CT scanners were performed for cross-platform validation. For algorithm evaluation, the iterative convergence is first shown, and peak-to-noise-ratio (PNR) and contrast-to-noise ratio (CNR) results are given with the cone-beam filtered backprojection (FDK) algorithm and the FDK results followed by median filtering (mFDK) as reference. The effect on spatial gradients and reconstruction artefacts is also investigated. The PNR curve illustrates that the results of SART  +  OS  +  TV finally converges to that of FDK but with less noise, which implies that the dose-OD calibration method for FDK is also applicable to the proposed algorithm. The CNR in selected regions-of-interest (ROIs) of SART  +  OS  +  TV results is almost double that of FDK and 50% higher than that of mFDK. The artefacts in SART  +  OS  +  TV results are still visible, but have been much suppressed with little spatial gradient loss. Based on the assessment, we can conclude that this hybrid SART  +  OS  +  TV algorithm outperforms both FDK and mFDK in denoising, preserving spatial dose gradients and reducing artefacts, and its effectiveness and efficiency are platform independent.

  6. WE-G-18A-04: 3D Dictionary Learning Based Statistical Iterative Reconstruction for Low-Dose Cone Beam CT Imaging

    SciTech Connect

    Bai, T; Yan, H; Shi, F; Jia, X; Jiang, Steve B.; Lou, Y; Xu, Q; Mou, X

    2014-06-15

    Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm in a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential

  7. Coronary Stent Artifact Reduction with an Edge-Enhancing Reconstruction Kernel – A Prospective Cross-Sectional Study with 256-Slice CT

    PubMed Central

    Tan, Stéphanie; Soulez, Gilles; Diez Martinez, Patricia; Larrivée, Sandra; Stevens, Louis-Mathieu; Goussard, Yves; Mansour, Samer; Chartrand-Lefebvre, Carl

    2016-01-01

    Purpose Metallic artifacts can result in an artificial thickening of the coronary stent wall which can significantly impair computed tomography (CT) imaging in patients with coronary stents. The objective of this study is to assess in vivo visualization of coronary stent wall and lumen with an edge-enhancing CT reconstruction kernel, as compared to a standard kernel. Methods This is a prospective cross-sectional study involving the assessment of 71 coronary stents (24 patients), with blinded observers. After 256-slice CT angiography, image reconstruction was done with medium-smooth and edge-enhancing kernels. Stent wall thickness was measured with both orthogonal and circumference methods, averaging thickness from diameter and circumference measurements, respectively. Image quality was assessed quantitatively using objective parameters (noise, signal to noise (SNR) and contrast to noise (CNR) ratios), as well as visually using a 5-point Likert scale. Results Stent wall thickness was decreased with the edge-enhancing kernel in comparison to the standard kernel, either with the orthogonal (0.97 ± 0.02 versus 1.09 ± 0.03 mm, respectively; p<0.001) or the circumference method (1.13 ± 0.02 versus 1.21 ± 0.02 mm, respectively; p = 0.001). The edge-enhancing kernel generated less overestimation from nominal thickness compared to the standard kernel, both with the orthogonal (0.89 ± 0.19 versus 1.00 ± 0.26 mm, respectively; p<0.001) and the circumference (1.06 ± 0.26 versus 1.13 ± 0.31 mm, respectively; p = 0.005) methods. The edge-enhancing kernel was associated with lower SNR and CNR, as well as higher background noise (all p < 0.001), in comparison to the medium-smooth kernel. Stent visual scores were higher with the edge-enhancing kernel (p<0.001). Conclusion In vivo 256-slice CT assessment of coronary stents shows that the edge-enhancing CT reconstruction kernel generates thinner stent walls, less overestimation from nominal thickness, and better image quality

  8. Effect of Radiation Dose Reduction and Reconstruction Algorithm on Image Noise, Contrast, Resolution, and Detectability of Subtle Hypoattenuating Liver Lesions at Multidetector CT: Filtered Back Projection versus a Commercial Model-based Iterative Reconstruction Algorithm.

    PubMed

    Solomon, Justin; Marin, Daniele; Roy Choudhury, Kingshuk; Patel, Bhavik; Samei, Ehsan

    2017-02-07

    Purpose To determine the effect of radiation dose and iterative reconstruction (IR) on noise, contrast, resolution, and observer-based detectability of subtle hypoattenuating liver lesions and to estimate the dose reduction potential of the IR algorithm in question. Materials and Methods This prospective, single-center, HIPAA-compliant study was approved by the institutional review board. A dual-source computed tomography (CT) system was used to reconstruct CT projection data from 21 patients into six radiation dose levels (12.5%, 25%, 37.5%, 50%, 75%, and 100%) on the basis of two CT acquisitions. A series of virtual liver lesions (five per patient, 105 total, lesion-to-liver prereconstruction contrast of -15 HU, 12-mm diameter) were inserted into the raw CT projection data and images were reconstructed with filtered back projection (FBP) (B31f kernel) and sinogram-affirmed IR (SAFIRE) (I31f-5 kernel). Image noise (pixel standard deviation), lesion contrast (after reconstruction), lesion boundary sharpness (average normalized gradient at lesion boundary), and contrast-to-noise ratio (CNR) were compared. Next, a two-alternative forced choice perception experiment was performed (16 readers [six radiologists, 10 medical physicists]). A linear mixed-effects statistical model was used to compare detection accuracy between FBP and SAFIRE and to estimate the radiation dose reduction potential of SAFIRE. Results Compared with FBP, SAFIRE reduced noise by a mean of 53% ± 5, lesion contrast by 12% ± 4, and lesion sharpness by 13% ± 10 but increased CNR by 89% ± 19. Detection accuracy was 2% higher on average with SAFIRE than with FBP (P = .03), which translated into an estimated radiation dose reduction potential (±95% confidence interval) of 16% ± 13. Conclusion SAFIRE increases detectability at a given radiation dose (approximately 2% increase in detection accuracy) and allows for imaging at reduced radiation dose (16% ± 13), while maintaining low

  9. A very fast iterative algorithm for TV-regularized image reconstruction with applications to low-dose and few-view CT

    NASA Astrophysics Data System (ADS)

    Kudo, Hiroyuki; Yamazaki, Fukashi; Nemoto, Takuya; Takaki, Keita

    2016-10-01

    This paper concerns iterative reconstruction for low-dose and few-view CT by minimizing a data-fidelity term regularized with the Total Variation (TV) penalty. We propose a very fast iterative algorithm to solve this problem. The algorithm derivation is outlined as follows. First, the original minimization problem is reformulated into the saddle point (primal-dual) problem by using the Lagrangian duality, to which we apply the first-order primal-dual iterative methods. Second, we precondition the iteration formula using the ramp filter of Filtered Backprojection (FBP) reconstruction algorithm in such a way that the problem solution is not altered. The resulting algorithm resembles the structure of so-called iterative FBP algorithm, and it converges to the exact minimizer of cost function very fast.

  10. Hydroelectric structures studies using 3-dimensional methods

    SciTech Connect

    Harrell, T.R.; Jones, G.V.; Toner, C.K. )

    1989-01-01

    Deterioration and degradation of aged, hydroelectric project structures can significantly affect the operation and safety of a project. In many cases, hydroelectric headworks (in particular) have complicated geometrical configurations, loading patterns and hence, stress conditions. An accurate study of such structures can be performed using 3-dimensional computer models. 3-D computer models can be used for both stability evaluation and for finite element stress analysis. Computer aided engineering processes facilitate the use of 3-D methods in both pre-processing and post-processing of data. Two actual project examples are used to emphasize the authors' points.

  11. A multireader diagnostic performance study of low-contrast detectability on a third-generation dual-source CT scanner: filtered back projection versus advanced modeled iterative reconstruction

    NASA Astrophysics Data System (ADS)

    Solomon, Justin; Mileto, Achille; Ramirez-Giraldo, Juan Carlos; Samei, Ehsan

    2015-03-01

    The purpose of this work was to compare CT low-contrast detectability between two reconstruction algorithms, filtered back-projection (FBP) and advanced modeled iterative reconstruction (ADMIRE). A phantom was designed with a range of low-contrast circular inserts representing 5 contrast levels and 3 sizes. The phantom was imaged on a third-generation dual-source CT scanner (SOMATOM Definition Force, Siemens Healthcare) under various dose levels (0.74 - 5.8 mGy CTDIVol). Images were reconstructed using different settings of slice thickness (0.6 - 5 mm) and reconstruction algorithms (FBP and ADMIRE with strength of 3-5) and were assessed by eleven blinded and independent readers using a two alternative forced choice (2AFC) detection experiment. A second observer experiment was further performed in which observers scored the images based on the total number of visible object groups. Detection performance increased with increasing contrast, size, dose, with accuracy ranging from 50% (i.e., guessing) to 87% with an average inter-observer variability of ±7%. The use of ADMIRE-3 increased performance by 5.2% resulting in an estimated dose reduction potential of 56-60%. The results from the second experiment also showed increased number of visible object groups for increasing dose, slice thickness, and ADMIRE strength. The score difference between FBP and ADMIRE was 0.9, 1.3, and 2.1 for ADMIRE strengths of 3, 4, and 5, respectively, resulting in estimated dose reduction potentials between 4-80%. Overall, the data indicated potential to image at reduced doses while maintaining comparable image quality when using ADMIRE compared to FBP.

  12. SU-E-J-150: Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

    SciTech Connect

    Ali, I; Ahmad, S; Alsbou, N

    2015-06-15

    Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases

  13. CT Pulmonary Angiography at Reduced Radiation Exposure and Contrast Material Volume Using Iterative Model Reconstruction and iDose4 Technique in Comparison to FBP

    PubMed Central

    Laqmani, Azien; Kurfürst, Maximillian; Butscheidt, Sebastian; Sehner, Susanne; Schmidt-Holtz, Jakob; Behzadi, Cyrus; Nagel, Hans Dieter; Adam, Gerhard; Regier, Marc

    2016-01-01

    Purpose To assess image quality of CT pulmonary angiography (CTPA) at reduced radiation exposure (RD-CTPA) and contrast medium (CM) volume using two different iterative reconstruction (IR) algorithms (iDose4 and iterative model reconstruction (IMR)) in comparison to filtered back projection (FBP). Materials and Methods 52 patients (body weight < 100 kg, mean BMI: 23.9) with suspected pulmonary embolism (PE) underwent RD-CTPA (tube voltage: 80 kV; mean CTDIvol: 1.9 mGy) using 40 ml CM. Data were reconstructed using FBP and two different IR algorithms (iDose4 and IMR). Subjective and objective image quality and conspicuity of PE were assessed in central, segmental, and subsegmental arteries. Results Noise reduction of 55% was achieved with iDose4 and of 85% with IMR compared to FBP. Contrast-to-noise ratio significantly increased with iDose4 and IMR compared to FBP (p<0.05). Subjective image quality was rated significantly higher at IMR reconstructions in comparison to iDose4 and FBP. Conspicuity of central and segmental PE significantly improved with the use of IMR. In subsegmental arteries, iDose4 was superior to IMR. Conclusions CTPA at reduced radiation exposure and contrast medium volume is feasible with the use of IMR, which provides improved image quality and conspicuity of pulmonary embolism in central and segmental arteries. PMID:27611448

  14. Patient-specific minimum-dose imaging protocols for statistical image reconstruction in C-arm cone-beam CT using correlated noise injection

    NASA Astrophysics Data System (ADS)

    Wang, A. S.; Stayman, J. W.; Otake, Y.; Khanna, A. J.; Gallia, G. L.; Siewerdsen, J. H.

    2014-03-01

    Purpose: A new method for accurately portraying the impact of low-dose imaging techniques in C-arm cone-beam CT (CBCT) is presented and validated, allowing identification of minimum-dose protocols suitable to a given imaging task on a patient-specific basis in scenarios that require repeat intraoperative scans. Method: To accurately simulate lower-dose techniques and account for object-dependent noise levels (x-ray quantum noise and detector electronics noise) and correlations (detector blur), noise of the proper magnitude and correlation was injected into the projections from an initial CBCT acquired at the beginning of a procedure. The resulting noisy projections were then reconstructed to yield low-dose preview (LDP) images that accurately depict the image quality at any level of reduced dose in both filtered backprojection and statistical image reconstruction. Validation studies were conducted on a mobile C-arm, with the noise injection method applied to images of an anthropomorphic head phantom and cadaveric torso across a range of lower-dose techniques. Results: Comparison of preview and real CBCT images across a full range of techniques demonstrated accurate noise magnitude (within ~5%) and correlation (matching noise-power spectrum, NPS). Other image quality characteristics (e.g., spatial resolution, contrast, and artifacts associated with beam hardening and scatter) were also realistically presented at all levels of dose and across reconstruction methods, including statistical reconstruction. Conclusion: Generating low-dose preview images for a broad range of protocols gives a useful method to select minimum-dose techniques that accounts for complex factors of imaging task, patient-specific anatomy, and observer preference. The ability to accurately simulate the influence of low-dose acquisition in statistical reconstruction provides an especially valuable means of identifying low-dose limits in a manner that does not rely on a model for the nonlinear

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

    PubMed Central

    Zhang, Hao; Han, Hao; Wang, Jing; Ma, Jianhua; Liu, Yan; Moore, William; Liang, Zhengrong

    2014-01-01

    Purpose: 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. Methods: 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. Results: 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

  16. High-Pitch, Low-Voltage and Low-Iodine-Concentration CT Angiography of Aorta: Assessment of Image Quality and Radiation Dose with Iterative Reconstruction

    PubMed Central

    Shen, Yanguang; Sun, Zhonghua; Xu, Lei; Li, Yu; Zhang, Nan; Yan, Zixu; Fan, Zhanming

    2015-01-01

    Objective To assess the image quality of aorta obtained by dual-source computed tomography angiography (DSCTA), performed with high pitch, low tube voltage, and low iodine concentration contrast medium (CM) with images reconstructed using iterative reconstruction (IR). Methods One hundred patients randomly allocated to receive one of two types of CM underwent DSCTA with the electrocardiogram-triggered Flash protocol. In the low-iodine group, 50 patients received CM containing 270 mg I/mL and were scanned at low tube voltage (100 kVp). In the high-iodine CM group, 50 patients received CM containing 370 mg I/mL and were scanned at the tube voltage (120 kVp). The filtered back projection (FBP) algorithm was used for reconstruction in both groups. In addition, the IR algorithm was used in the low-iodine group. Image quality of the aorta was analyzed subjectively by a 3-point grading scale and objectively by measuring the CT attenuation in terms of the signal- and contrast-to-noise ratios (SNR and CNR, respectively). Radiation and CM doses were compared. Results The CT attenuation, subjective image quality assessment, SNR, and CNR of various aortic regions of interest did not differ significantly between two groups. In the low-iodine group, images reconstructed by FBP and IR demonstrated significant differences in image noise, SNR, and CNR (p<0.05). The low-iodine group resulted in 34.3% less radiation (4.4 ± 0.5 mSv) than the high-iodine group (6.7 ± 0.6 mSv), and 27.3% less iodine weight (20.36 ± 2.65 g) than the high-iodine group (28 ± 1.98 g). Observers exhibited excellent agreement on the aortic image quality scores (κ = 0.904). Conclusions CT images of aorta could be obtained within 2 s by using a DSCT Flash protocol with low tube voltage, IR, and low-iodine-concentration CM. Appropriate contrast enhancement was achieved while maintaining good image quality and decreasing the radiation and iodine doses. PMID:25643353

  17. Improved dose calculation accuracy for low energy brachytherapy by optimizing dual energy CT imaging protocols for noise reduction using sinogram affirmed iterative reconstruction.

    PubMed

    Landry, Guillaume; Gaudreault, Mathieu; van Elmpt, Wouter; Wildberger, Joachim E; Verhaegen, Frank

    2016-03-01

    The goal of this study was to evaluate the noise reduction achievable from dual energy computed tomography (CT) imaging (DECT) using filtered backprojection (FBP) and iterative image reconstruction algorithms combined with increased imaging exposure. We evaluated the data in the context of imaging for brachytherapy dose calculation, where accurate quantification of electron density ρe and effective atomic number Zeff is beneficial. A dual source CT scanner was used to scan a phantom containing tissue mimicking inserts. DECT scans were acquired at 80 kVp/140Sn kVp (where Sn stands for tin filtration) and 100 kVp/140Sn kVp, using the same values of the CT dose index CTDIvol for both settings as a measure for the radiation imaging exposure. Four CTDIvol levels were investigated. Images were reconstructed using FBP and sinogram affirmed iterative reconstruction (SAFIRE) with strength 1,3 and 5. From DECT scans two material quantities were derived, Zeff and ρe. DECT images were used to assign material types and the amount of improperly assigned voxels was quantified for each protocol. The dosimetric impact of improperly assigned voxels was evaluated with Geant4 Monte Carlo (MC) dose calculations for an (125)I source in numerical phantoms. Standard deviations for Zeff and ρe were reduced up to a factor ∼2 when using SAFIRE with strength 5 compared to FBP. Standard deviations on Zeff and ρe as low as 0.15 and 0.006 were achieved for the muscle insert representing typical soft tissue using a CTDIvol of 40 mGy and 3mm slice thickness. Dose calculation accuracy was generally improved when using SAFIRE. Mean (maximum absolute) dose errors of up to 1.3% (21%) with FBP were reduced to less than 1% (6%) with SAFIRE at a CTDIvol of 10 mGy. Using a CTDIvol of 40mGy and SAFIRE yielded mean dose calculation errors of the order of 0.6% which was the MC dose calculation precision in this study and no error was larger than ±2.5% as opposed to errors of up to -4% with FPB. This

  18. A Simple 3-Dimensional Printed Aid for a Corrective Palmar Opening Wedge Osteotomy of the Distal Radius.

    PubMed

    Honigmann, Philipp; Thieringer, Florian; Steiger, Regula; Haefeli, Mathias; Schumacher, Ralf; Henning, Julia

    2016-03-01

    The reconstruction of malunited distal radius fractures is often challenging. Virtual planning techniques and guides for drilling and resection have been used for several years to achieve anatomic reconstruction. These guides have the advantage of leading to better operative results and faster surgery. Here, we describe a technique using a simple implant independent 3-dimensional printed drill guide and template to simplify the surgical reconstruction of a malunited distal radius fracture.

  19. Computer-aided diagnosis in CT colonography: detection of polyps based on geometric and texture features

    NASA Astrophysics Data System (ADS)

    Yoshida, Hiroyuki; Naeppi, Janne J.; Frimmel, Hans; Dachman, Abraham H.

    2002-05-01

    A computer-aided diagnosis scheme for the detection of colonic polyps in CT colonography has been developed, and its performance has been assessed based on clinical cases with colonoscopy-confirmed polyps. In the scheme, the colon was automatically segmented by use of knowledge-guided segmentation from 3-dimensional isotropic volumes reconstructed from axial CT slices in CT colonography. Polyp candidates are detected by first computing of 3-dimensional geometric features that characterize polyps, and then segmenting of connected components corresponding to suspicious regions by hysteresis thresholding and fuzzy clustering based on these geometric features. False-positive detections are reduced by computation of 3-dimensional texture features characterizing the internal structures of the polyp candidates, followed by application of discriminant analysis to the feature space generated by the geometric and texture features. We applied our scheme to 43 CT colonographic cases with cleansed colon, including 12 polyps larger than 5 mm. In a by-dataset analysis, the CAD scheme yielded a sensitivity of 95% with 1.2 false positives per data set. The false negative was one of the two polyps in a single patient. Consequently, in by-patient analysis, our method yielded 100% sensitivity with 2.0 false positives per patient. The results indicate that our CAD scheme has the potential to detect clinically important polyp cases with a high sensitivity and a relatively low false-positive rate.

  20. 3-Dimensional quantitative detection of nanoparticle content in biological tissue samples after local cancer treatment

    NASA Astrophysics Data System (ADS)

    Rahn, Helene; Alexiou, Christoph; Trahms, Lutz; Odenbach, Stefan

    2014-06-01

    X-ray computed tomography is nowadays used for a wide range of applications in medicine, science and technology. X-ray microcomputed tomography (XμCT) follows the same principles used for conventional medical CT scanners, but improves the spatial resolution to a few micrometers. We present an example of an application of X-ray microtomography, a study of 3-dimensional biodistribution, as along with the quantification of nanoparticle content in tumoral tissue after minimally invasive cancer therapy. One of these minimal invasive cancer treatments is magnetic drug targeting, where the magnetic nanoparticles are used as controllable drug carriers. The quantification is based on a calibration of the XμCT-equipment. The developed calibration procedure of the X-ray-μCT-equipment is based on a phantom system which allows the discrimination between the various gray values of the data set. These phantoms consist of a biological tissue substitute and magnetic nanoparticles. The phantoms have been studied with XμCT and have been examined magnetically. The obtained gray values and nanoparticle concentration lead to a calibration curve. This curve can be applied to tomographic data sets. Accordingly, this calibration enables a voxel-wise assignment of gray values in the digital tomographic data set to nanoparticle content. Thus, the calibration procedure enables a 3-dimensional study of nanoparticle distribution as well as concentration.

  1. A three-dimensional weighted cone beam filtered backprojection (CB-FBP) algorithm for image reconstruction in volumetric CT under a circular source trajectory

    NASA Astrophysics Data System (ADS)

    Tang, Xiangyang; Hsieh, Jiang; Hagiwara, Akira; Nilsen, Roy A.; Thibault, Jean-Baptiste; Drapkin, Evgeny

    2005-08-01

    The original FDK algorithm proposed for cone beam (CB) image reconstruction under a circular source trajectory has been extensively employed in medical and industrial imaging applications. With increasing cone angle, CB artefacts in images reconstructed by the original FDK algorithm deteriorate, since the circular trajectory does not satisfy the so-called data sufficiency condition (DSC). A few 'circular plus' trajectories have been proposed in the past to help the original FDK algorithm to reduce CB artefacts by meeting the DSC. However, the circular trajectory has distinct advantages over other scanning trajectories in practical CT imaging, such as head imaging, breast imaging, cardiac, vascular and perfusion applications. In addition to looking into the DSC, another insight into the CB artefacts existing in the original FDK algorithm is the inconsistency between conjugate rays that are 180° apart in view angle (namely conjugate ray inconsistency). The conjugate ray inconsistency is pixel dependent, varying dramatically over pixels within the image plane to be reconstructed. However, the original FDK algorithm treats all conjugate rays equally, resulting in CB artefacts that can be avoided if appropriate weighting strategies are exercised. Along with an experimental evaluation and verification, a three-dimensional (3D) weighted axial cone beam filtered backprojection (CB-FBP) algorithm is proposed in this paper for image reconstruction in volumetric CT under a circular source trajectory. Without extra trajectories supplemental to the circular trajectory, the proposed algorithm applies 3D weighting on projection data before 3D backprojection to reduce conjugate ray inconsistency by suppressing the contribution from one of the conjugate rays with a larger cone angle. Furthermore, the 3D weighting is dependent on the distance between the reconstruction plane and the central plane determined by the circular trajectory. The proposed 3D weighted axial CB-FBP algorithm

  2. Use of 3-dimensional computed tomography to detect a barium-masked fish bone causing esophageal perforation.

    PubMed

    Tsukiyama, Atsushi; Tagami, Takashi; Kim, Shiei; Yokota, Hiroyuki

    2014-01-01

    Computed tomography (CT) is useful for evaluating esophageal foreign bodies and detecting perforation. However, when evaluation is difficult owing to the previous use of barium as a contrast medium, 3-dimensional CT may facilitate accurate diagnosis. A 49-year-old man was transferred to our hospital with the diagnosis of esophageal perforation. Because barium had been used as a contrast medium for an esophagram performed at a previous hospital, horizontal CT and esophageal endoscopy could not be able to identify the foreign body or characterize the lesion. However, 3-dimensional CT clearly revealed an L-shaped foreign body and its anatomical relationships in the mediastinum. Accordingly, we removed the foreign body using an upper gastrointestinal endoscope. The foreign body was the premaxillary bone of a sea bream. The patient was discharged without complications.

  3. Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

    SciTech Connect

    Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J.; Kuncic, Zdenka

    2014-04-15

    Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

  4. Towards clinical application of a Laplace operator-based region of interest reconstruction algorithm in C-arm CT.

    PubMed

    Xia, Yan; Hofmann, Hannes; Dennerlein, Frank; Mueller, Kerstin; Schwemmer, Chris; Bauer, Sebastian; Chintalapani, Gouthami; Chinnadurai, Ponraj; Hornegger, Joachim; Maier, Andreas

    2014-03-01

    It is known that a reduction of the field-of-view in 3-D X-ray imaging is proportional to a reduction in radiation dose. The resulting truncation, however, is incompatible with conventional reconstruction algorithms. Recently, a novel method for region of interest reconstruction that uses neither prior knowledge nor extrapolation has been published, named approximated truncation robust algorithm for computed tomography (ATRACT). It is based on a decomposition of the standard ramp filter into a 2-D Laplace filtering and a 2-D Radon-based residual filtering step. In this paper, we present two variants of the original ATRACT. One is based on expressing the residual filter as an efficient 2-D convolution with an analytically derived kernel. The second variant is to apply ATRACT in 1-D to further reduce computational complexity. The proposed algorithms were evaluated by using a reconstruction benchmark, as well as two clinical data sets. The results are encouraging since the proposed algorithms achieve a speed-up factor of up to 245 compared to the 2-D Radon-based ATRACT. Reconstructions of high accuracy are obtained, e.g., even real-data reconstruction in the presence of severe truncation achieve a relative root mean square error of as little as 0.92% with respect to nontruncated data.

  5. Model-based iterative reconstruction for flat-panel cone-beam CT with focal spot blur, detector blur, and correlated noise

    NASA Astrophysics Data System (ADS)

    Tilley, Steven, II; Siewerdsen, Jeffrey H.; Webster Stayman, J.

    2016-01-01

    While model-based reconstruction methods have been successfully applied to flat-panel cone-beam CT (FP-CBCT) systems, typical implementations ignore both spatial correlations in the projection data as well as system blurs due to the detector and focal spot in the x-ray source. In this work, we develop a forward model for flat-panel-based systems that includes blur and noise correlation associated with finite focal spot size and an indirect detector (e.g. scintillator). This forward model is used to develop a staged reconstruction framework where projection data are deconvolved and log-transformed, followed by a generalized least-squares reconstruction that utilizes a non-diagonal statistical weighting to account for the correlation that arises from the acquisition and data processing chain. We investigate the performance of this novel reconstruction approach in both simulated data and in CBCT test-bench data. In comparison to traditional filtered backprojection and model-based methods that ignore noise correlation, the proposed approach yields a superior noise-resolution tradeoff. For example, for a system with 0.34 mm FWHM scintillator blur and 0.70 FWHM focal spot blur, using the correlated noise model instead of an uncorrelated noise model increased resolution by 42% (with variance matched at 6.9  ×  10-8 mm-2). While this advantage holds across a wide range of systems with differing blur characteristics, the improvements are greatest for systems where source blur is larger than detector blur.

  6. Diagnostic Accuracy of CT Enterography for Active Inflammatory Terminal Ileal Crohn Disease: Comparison of Full-Dose and Half-Dose Images Reconstructed with FBP and Half-Dose Images with SAFIRE.

    PubMed

    Gandhi, Namita S; Baker, Mark E; Goenka, Ajit H; Bullen, Jennifer A; Obuchowski, Nancy A; Remer, Erick M; Coppa, Christopher P; Einstein, David; Feldman, Myra K; Kanmaniraja, Devaraju; Purysko, Andrei S; Vahdat, Noushin; Primak, Andrew N; Karim, Wadih; Herts, Brian R

    2016-08-01

    Purpose To compare the diagnostic accuracy and image quality of computed tomographic (CT) enterographic images obtained at half dose and reconstructed with filtered back projection (FBP) and sinogram-affirmed iterative reconstruction (SAFIRE) with those of full-dose CT enterographic images reconstructed with FBP for active inflammatory terminal or neoterminal ileal Crohn disease. Materials and Methods This retrospective study was compliant with HIPAA and approved by the institutional review board. The requirement to obtain informed consent was waived. Ninety subjects (45 with active terminal ileal Crohn disease and 45 without Crohn disease) underwent CT enterography with a dual-source CT unit. The reference standard for confirmation of active Crohn disease was active terminal ileal Crohn disease based on ileocolonoscopy or established Crohn disease and imaging features of active terminal ileal Crohn disease. Data from both tubes were reconstructed with FBP (100% exposure); data from the primary tube (50% exposure) were reconstructed with FBP and SAFIRE strengths 3 and 4, yielding four datasets per CT enterographic examination. The mean volume CT dose index (CTDIvol) and size-specific dose estimate (SSDE) at full dose were 13.1 mGy (median, 7.36 mGy) and 15.9 mGy (median, 13.06 mGy), respectively, and those at half dose were 6.55 mGy (median, 3.68 mGy) and 7.95 mGy (median, 6.5 mGy). Images were subjectively evaluated by eight radiologists for quality and diagnostic confidence for Crohn disease. Areas under the receiver operating characteristic curves (AUCs) were estimated, and the multireader, multicase analysis of variance method was used to compare reconstruction methods on the basis of a noninferiority margin of 0.05. Results The mean AUCs with half-dose scans (FBP, 0.908; SAFIRE 3, 0.935; SAFIRE 4, 0.924) were noninferior to the mean AUC with full-dose FBP scans (0.908; P < .003). The proportion of images with inferior quality was significantly higher with all

  7. TU-G-204-05: The Effects of CT Acquisition and Reconstruction Conditions On Computed Texture Feature Values of Lung Lesions

    SciTech Connect

    Lo, P; Young, S; Kim, G; Hoffman, J; Brown, M; McNitt-Gray, M

    2015-06-15

    Purpose: Texture features have been investigated as a biomarker of response and malignancy. Because these features reflect local differences in density, they may be influenced by acquisition and reconstruction parameters. The purpose of this study was to investigate the effects of radiation dose level and reconstruction method on features derived from lung lesions. Methods: With IRB approval, 33 lung tumor cases were identified from clinically indicated thoracic CT scans in which the raw projection (sinogram) data were available. Based on a previously-published technique, noise was added to the raw data to simulate reduced-dose versions of each case at 25%, 10% and 3% of the original dose. Original and simulated reduced dose projection data were reconstructed with conventional and two iterative-reconstruction settings, yielding 12 combinations of dose/recon conditions. One lesion from each case was contoured. At the reference condition (full dose, conventional recon), 17 lesions were randomly selected for repeat contouring (repeatability). For each lesion at each dose/recon condition, 151 texture measures were calculated. A paired differences approach was employed to compare feature variation from repeat contours at the reference condition to the variation observed in other dose/recon conditions (reproducibility). The ratio of standard deviation of the reproducibility to repeatability was used as the variation measure for each feature. Results: The mean variation (standard deviation) across dose levels and kernel was significantly different with a ratio of 2.24 (±5.85) across texture features (p=0.01). The mean variation (standard deviation) across dose levels with conventional recon was also significantly different with 2.30 (7.11) (p=0.025). The mean variation across reconstruction settings of original dose has a trend in showing difference with 1.35 (2.60) among all features (p=0.09). Conclusion: Texture features varied considerably with variations in dose and

  8. Cardiothoracic Applications of 3-dimensional Printing.

    PubMed

    Giannopoulos, Andreas A; Steigner, Michael L; George, Elizabeth; Barile, Maria; Hunsaker, Andetta R; Rybicki, Frank J; Mitsouras, Dimitris

    2016-09-01

    Medical 3-dimensional (3D) printing is emerging as a clinically relevant imaging tool in directing preoperative and intraoperative planning in many surgical specialties and will therefore likely lead to interdisciplinary collaboration between engineers, radiologists, and surgeons. Data from standard imaging modalities such as computed tomography, magnetic resonance imaging, echocardiography, and rotational angiography can be used to fabricate life-sized models of human anatomy and pathology, as well as patient-specific implants and surgical guides. Cardiovascular 3D-printed models can improve diagnosis and allow for advanced preoperative planning. The majority of applications reported involve congenital heart diseases and valvular and great vessels pathologies. Printed models are suitable for planning both surgical and minimally invasive procedures. Added value has been reported toward improving outcomes, minimizing perioperative risk, and developing new procedures such as transcatheter mitral valve replacements. Similarly, thoracic surgeons are using 3D printing to assess invasion of vital structures by tumors and to assist in diagnosis and treatment of upper and lower airway diseases. Anatomic models enable surgeons to assimilate information more quickly than image review, choose the optimal surgical approach, and achieve surgery in a shorter time. Patient-specific 3D-printed implants are beginning to appear and may have significant impact on cosmetic and life-saving procedures in the future. In summary, cardiothoracic 3D printing is rapidly evolving and may be a potential game-changer for surgeons. The imager who is equipped with the tools to apply this new imaging science to cardiothoracic care is thus ideally positioned to innovate in this new emerging imaging modality.

  9. In vitro measurement of muscle volume with 3-dimensional ultrasound.

    PubMed

    Delcker, A; Walker, F; Caress, J; Hunt, C; Tegeler, C

    1999-05-01

    The aim was to test the accuracy of muscle volume measurements with a new 3-dimensional (3-D) ultrasound system, which allows a freehand scanning of the transducer with an improved quality of the ultrasound images and therefore the outlines of the muscles. Five resected cadaveric hand muscles were insonated and the muscle volumes calculated by 3-D reconstructions of the acquired 2-D ultrasound sections. Intra-reader, inter-reader and follow-up variability were calculated, as well as the volume of the muscle tissue measured by water displacement. In the results, 3-D ultrasound and water displacement measurements showed an average deviation of 10.1%; Data of 3-D ultrasound measurements were: intra-reader variability 2.8%; inter-reader variability 2.4% and follow-up variability 2.3%. 3-D measurements of muscle volume are valid and reliable. Serial sonographic measurements of muscle may be able to quantitate changes in muscle volume that occur in disease and recovery.

  10. Analysis of the Geometry of the Distal Femur and Proximal Tibia in the Osteoarthritic Knee: A 3D Reconstruction CT Scan Based Study of 449 Cases

    PubMed Central

    Lyras, Dimitrios N.; Loucks, Craig; Greenhow, Robert

    2016-01-01

    Background: The aim of this study is to evaluate the geometry of the distal femur and the proximal tibia in the osteoarthritic knee using 3D reconstructive CT scan imaging. Methods: 449 patients with knee osteoarthritis were treated surgically in our center with patient-specific technology total knee arthroplasty. Preoperatively, all the patients underwent a CT scan according to a standard protocol. Using this database, the Hip-Knee-Angle (HKA), the Femur Valgus Angle (FVA), the Tibia Varus Angle (TVA), the Posterior Tibia Slope (PTS), and the angle between the posterior condylar axis and the anatomical transepicondylar axis (PCA) for each patient were recorded and statistically evaluated. Results: In overall, the mean HKA angle was 177.3±5.55, the mean FVA angle was 3.19±2.08, the mean TVA was 3.28±2.35, the PTS angle was 9.02±3.46, and the PCA angle was 2.86±0.78. Evaluation of the correlations between HKA and PCA (r=0.035), HKA and PTS (r=-0.047), and PCA and PTS (r=0.05) showed non-significant relationships (P=0.46, P=0.32, and P=0.29 respectively). No significant differences were revealed from the comparison of male patients with female patients, regarding the mean HKA, FVA, TVA, PTS, and PCA. Conclusion: The posterior condylar axis is a well-defined but not a reliable axis, while the transepicondylar and the anteroposterior are reliable, but not easily defined axes. Given the large ranges and standard deviations of the location of posterior condylar axis, and the important inter- and intraobserver variability in the intraoperative location of the transepicondylar and the anteroposterior axes, the use of a preoperative 3D CT scan is recommended. PMID:27200387

  11. Three-dimensional visualization and characterization of bone structure using reconstructed in-vitro μCT images: A pilot study for bone microarchitecture analysis

    SciTech Connect

    Latief, Fourier Dzar Eljabbar; Dewi, Dyah Ekashanti Octorina; Shari, Mohd Aliff Bin Mohd

    2014-03-24

    Micro Computed Tomography (μCT) has been largely used to perform micrometer scale imaging of specimens, bone biopsies and small animals for the study of porous or cavity-containing objects. One of its favored applications is for assessing structural properties of bone. In this research, we perform a pilot study to visualize and characterize bone structure of a chicken bone thigh, as well as to delineate its cortical and trabecular bone regions. We utilize an In-Vitro μCT scanner Skyscan 1173 to acquire a three dimensional image data of a chicken bone thigh. The thigh was scanned using X-ray voltage of 45 kV and current of 150 μA. The reconstructed images have spatial resolution of 142.50 μm/pixel. Using image processing and analysis e.i segmentation by thresholding the gray values (which represent the pseudo density) and binarizing the images, we were able to visualize each part of the bone, i.e., the cortical and trabecular regions. Total volume of the bone is 4663.63 mm{sup 3}, and the surface area of the bone is 7913.42 mm{sup 2}. The volume of the cortical is approximately 1988.62 mm{sup 3} which is nearly 42.64% of the total bone volume. This pilot study has confirmed that the μCT is capable of quantifying 3D bone structural properties and defining its regions separately. For further development, these results can be improved for understanding the pathophysiology of bone abnormality, testing the efficacy of pharmaceutical intervention, or estimating bone biomechanical properties.

  12. Three-dimensional visualization and characterization of bone structure using reconstructed in-vitro μCT images: A pilot study for bone microarchitecture analysis

    NASA Astrophysics Data System (ADS)

    Latief, Fourier Dzar Eljabbar; Dewi, Dyah Ekashanti Octorina; Shari, Mohd Aliff Bin Mohd

    2014-03-01

    Micro Computed Tomography (μCT) has been largely used to perform micrometer scale imaging of specimens, bone biopsies and small animals for the study of porous or cavity-containing objects. One of its favored applications is for assessing structural properties of bone. In this research, we perform a pilot study to visualize and characterize bone structure of a chicken bone thigh, as well as to delineate its cortical and trabecular bone regions. We utilize an In-Vitro μCT scanner Skyscan 1173 to acquire a three dimensional image data of a chicken bone thigh. The thigh was scanned using X-ray voltage of 45 kV and current of 150 μA. The reconstructed images have spatial resolution of 142.50 μm/pixel. Using image processing and analysis e.i segmentation by thresholding the gray values (which represent the pseudo density) and binarizing the images, we were able to visualize each part of the bone, i.e., the cortical and trabecular regions. Total volume of the bone is 4663.63 mm3, and the surface area of the bone is 7913.42 mm2. The volume of the cortical is approximately 1988.62 mm3 which is nearly 42.64% of the total bone volume. This pilot study has confirmed that the μCT is capable of quantifying 3D bone structural properties and defining its regions separately. For further development, these results can be improved for understanding the pathophysiology of bone abnormality, testing the efficacy of pharmaceutical intervention, or estimating bone biomechanical properties.

  13. 3-D reconstruction and virtual ductoscopy of high-grade ductal carcinoma in situ of the breast with casting type calcifications using refraction-based X-ray CT.

    PubMed

    Ichihara, Shu; Ando, Masami; Maksimenko, Anton; Yuasa, Tetsuya; Sugiyama, Hiroshi; Hashimoto, Eiko; Yamasaki, Katsuhito; Mori, Kensaku; Arai, Yoshinori; Endo, Tokiko

    2008-01-01

    Stereomicroscopic observations of thick sections, or three-dimensional (3-D) reconstructions from serial sections, have provided insights into histopathology. However, they generally require time-consuming and laborious procedures. Recently, we have developed a new algorithm for refraction-based X-ray computed tomography (CT). The aim of this study is to apply this emerging technology to visualize the 3-D structure of a high-grade ductal carcinomas in situ (DCIS) of the breast. The high-resolution two-dimensional images of the refraction-based CT were validated by comparing them with the sequential histological sections. Without adding any contrast medium, the new CT showed strong contrast and was able to depict the non-calcified fine structures such as duct walls and intraductal carcinoma itself, both of which were barely visible in a conventional absorption-based CT. 3-D reconstruction and virtual endoscopy revealed that the high-grade DCIS was located within the dichotomatous branches of the ducts. Multiple calcifications occurred in the necrotic core of the continuous DCIS, resulting in linear and branching (casting type) calcifications, a hallmark of high-grade DCIS on mammograms. In conclusion, refraction-based X-ray CT approaches the low-power light microscopic view of the histological sections. It provides high quality slice data for 3-D reconstruction and virtual ductosocpy.

  14. Simulation and experimental studies of three-dimensional (3D) image reconstruction from insufficient sampling data based on compressed-sensing theory for potential applications to dental cone-beam CT

    NASA Astrophysics Data System (ADS)

    Je, U. K.; Lee, M. S.; Cho, H. S.; Hong, D. K.; Park, Y. O.; Park, C. K.; Cho, H. M.; Choi, S. I.; Woo, T. H.

    2015-06-01

    In practical applications of three-dimensional (3D) tomographic imaging, there are often challenges for image reconstruction from insufficient sampling data. In computed tomography (CT), for example, image reconstruction from sparse views and/or limited-angle (<360°) views would enable fast scanning with reduced imaging doses to the patient. In this study, we investigated and implemented a reconstruction algorithm based on the compressed-sensing (CS) theory, which exploits the sparseness of the gradient image with substantially high accuracy, for potential applications to low-dose, high-accurate dental cone-beam CT (CBCT). We performed systematic simulation works to investigate the image characteristics and also performed experimental works by applying the algorithm to a commercially-available dental CBCT system to demonstrate its effectiveness for image reconstruction in insufficient sampling problems. We successfully reconstructed CBCT images of superior accuracy from insufficient sampling data and evaluated the reconstruction quality quantitatively. Both simulation and experimental demonstrations of the CS-based reconstruction from insufficient data indicate that the CS-based algorithm can be applied directly to current dental CBCT systems for reducing the imaging doses and further improving the image quality.

  15. Maximum-likelihood joint image reconstruction and motion estimation with misaligned attenuation in TOF-PET/CT

    NASA Astrophysics Data System (ADS)

    Bousse, Alexandre; Bertolli, Ottavia; Atkinson, David; Arridge, Simon; Ourselin, Sébastien; Hutton, Brian F.; Thielemans, Kris

    2016-02-01

    This work is an extension of our recent work on joint activity reconstruction/motion estimation (JRM) from positron emission tomography (PET) data. We performed JRM by maximization of the penalized log-likelihood in which the probabilistic model assumes that the same motion field affects both the activity distribution and the attenuation map. Our previous results showed that JRM can successfully reconstruct the activity distribution when the attenuation map is misaligned with the PET data, but converges slowly due to the significant cross-talk in the likelihood. In this paper, we utilize time-of-flight PET for JRM and demonstrate that the convergence speed is significantly improved compared to JRM with conventional PET data.

  16. Clinical application of low-dose phase contrast breast CT: methods for the optimization of the reconstruction workflow.

    PubMed

    Pacilè, S; Brun, F; Dullin, C; Nesterest, Y I; Dreossi, D; Mohammadi, S; Tonutti, M; Stacul, F; Lockie, D; Zanconati, F; Accardo, A; Tromba, G; Gureyev, T E

    2015-08-01

    Results are presented of a feasibility study of three-dimensional X-ray tomographic mammography utilising in-line phase contrast. Experiments were performed at SYRMEP beamline of Elettra synchrotron. A specially designed plastic phantom and a mastectomy sample containing a malignant lesion were used to study the reconstructed image quality as a function of different image processing operations. Detailed evaluation and optimization of image reconstruction workflows have been carried out using combinations of several advanced computed tomography algorithms with different pre-processing and post-processing steps. Special attention was paid to the effect of phase retrieval on the diagnostic value of the reconstructed images. A number of objective image quality indices have been applied for quantitative evaluation of the results, and these were compared with subjective assessments of the same images by three experienced radiologists and one pathologist. The outcomes of this study provide practical guidelines for the optimization of image processing workflows in synchrotron-based phase-contrast mammo-tomography.

  17. Clinical application of low-dose phase contrast breast CT: methods for the optimization of the reconstruction workflow

    PubMed Central

    Pacilè, S.; Brun, F.; Dullin, C.; Nesterest, Y. I.; Dreossi, D.; Mohammadi, S.; Tonutti, M.; Stacul, F.; Lockie, D.; Zanconati, F.; Accardo, A.; Tromba, G.; Gureyev, T. E.

    2015-01-01

    Results are presented of a feasibility study of three-dimensional X-ray tomographic mammography utilising in-line phase contrast. Experiments were performed at SYRMEP beamline of Elettra synchrotron. A specially designed plastic phantom and a mastectomy sample containing a malignant lesion were used to study the reconstructed image quality as a function of different image processing operations. Detailed evaluation and optimization of image reconstruction workflows have been carried out using combinations of several advanced computed tomography algorithms with different pre-processing and post-processing steps. Special attention was paid to the effect of phase retrieval on the diagnostic value of the reconstructed images. A number of objective image quality indices have been applied for quantitative evaluation of the results, and these were compared with subjective assessments of the same images by three experienced radiologists and one pathologist. The outcomes of this study provide practical guidelines for the optimization of image processing workflows in synchrotron-based phase-contrast mammo-tomography. PMID:26309770

  18. 3-dimensional orthodontics visualization system with dental study models and orthopantomograms

    NASA Astrophysics Data System (ADS)

    Zhang, Hua; Ong, S. H.; Foong, K. W. C.; Dhar, T.

    2005-04-01

    The aim of this study is to develop a system that provides 3-dimensional visualization of orthodontic treatments. Dental plaster models and corresponding orthopantomogram (dental panoramic tomogram) are first digitized and fed into the system. A semi-auto segmentation technique is applied to the plaster models to detect the dental arches, tooth interstices and gum margins, which are used to extract individual crown models. 3-dimensional representation of roots, generated by deforming generic tooth models with orthopantomogram using radial basis functions, is attached to corresponding crowns to enable visualization of complete teeth. An optional algorithm to close the gaps between deformed roots and actual crowns by using multi-quadratic radial basis functions is also presented, which is capable of generating smooth mesh representation of complete 3-dimensional teeth. User interface is carefully designed to achieve a flexible system with as much user friendliness as possible. Manual calibration and correction is possible throughout the data processing steps to compensate occasional misbehaviors of automatic procedures. By allowing the users to move and re-arrange individual teeth (with their roots) on a full dentition, this orthodontic visualization system provides an easy and accurate way of simulation and planning of orthodontic treatment. Its capability of presenting 3-dimensional root information with only study models and orthopantomogram is especially useful for patients who do not undergo CT scanning, which is not a routine procedure in most orthodontic cases.

  19. Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: application to high-quality head imaging

    NASA Astrophysics Data System (ADS)

    Dang, H.; Stayman, J. W.; Sisniega, A.; Xu, J.; Zbijewski, W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

    2015-08-01

    Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ~40-80 HU, size  >  1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution, CNR = 11.9 compared to CNR = 5.6 and CNR = 9.9, respectively) and substantially reduced image noise especially in challenging regions such as skull base. The results support the hypothesis that with high-fidelity artifact correction and statistical reconstruction using an accurate post-artifact-correction noise model, FPD-CBCT can achieve image quality allowing reliable detection of intracranial

  20. 3D inpatient dose reconstruction from the PET-CT imaging of {sup 90}Y microspheres for metastatic cancer to the liver: Feasibility study

    SciTech Connect

    Fourkal, E.; Veltchev, I.; Lin, M.; Meyer, J.; Koren, S.; Doss, M.; Yu, J. Q.

    2013-08-15

    Purpose: The introduction of radioembolization with microspheres represents a significant step forward in the treatment of patients with metastatic disease to the liver. This technique uses semiempirical formulae based on body surface area or liver and target volumes to calculate the required total activity for a given patient. However, this treatment modality lacks extremely important information, which is the three-dimensional (3D) dose delivered by microspheres to different organs after their administration. The absence of this information dramatically limits the clinical efficacy of this modality, specifically the predictive power of the treatment. Therefore, the aim of this study is to develop a 3D dose calculation technique that is based on the PET imaging of the infused microspheres.Methods: The Fluka Monte Carlo code was used to calculate the voxel dose kernel for {sup 90}Y source with voxel size equal to that of the PET scan. The measured PET activity distribution was converted to total activity distribution for the subsequent convolution with the voxel dose kernel to obtain the 3D dose distribution. In addition, dose-volume histograms were generated to analyze the dose to the tumor and critical structures.Results: The 3D inpatient dose distribution can be reconstructed from the PET data of a patient scanned after the infusion of microspheres. A total of seven patients have been analyzed so far using the proposed reconstruction method. Four patients underwent treatment with SIR-Spheres for liver metastases from colorectal cancer and three patients were treated with Therasphere for hepatocellular cancer. A total of 14 target tumors were contoured on post-treatment PET-CT scans for dosimetric evaluation. Mean prescription activity was 1.7 GBq (range: 0.58–3.8 GBq). The resulting mean maximum measured dose to targets was 167 Gy (range: 71–311 Gy). Mean minimum dose to 70% of target (D70) was 68 Gy (range: 25–155 Gy). Mean minimum dose to 90% of target

  1. Incorporating 3-dimensional models in online articles

    PubMed Central

    Cevidanes, Lucia H. S.; Ruellasa, Antonio C. O.; Jomier, Julien; Nguyen, Tung; Pieper, Steve; Budin, Francois; Styner, Martin; Paniagua, Beatriz

    2015-01-01

    Introduction The aims of this article were to introduce the capability to view and interact with 3-dimensional (3D) surface models in online publications, and to describe how to prepare surface models for such online 3D visualizations. Methods Three-dimensional image analysis methods include image acquisition, construction of surface models, registration in a common coordinate system, visualization of overlays, and quantification of changes. Cone-beam computed tomography scans were acquired as volumetric images that can be visualized as 3D projected images or used to construct polygonal meshes or surfaces of specific anatomic structures of interest. The anatomic structures of interest in the scans can be labeled with color (3D volumetric label maps), and then the scans are registered in a common coordinate system using a target region as the reference. The registered 3D volumetric label maps can be saved in .obj, .ply, .stl, or .vtk file formats and used for overlays, quantification of differences in each of the 3 planes of space, or color-coded graphic displays of 3D surface distances. Results All registered 3D surface models in this study were saved in .vtk file format and loaded in the Elsevier 3D viewer. In this study, we describe possible ways to visualize the surface models constructed from cone-beam computed tomography images using 2D and 3D figures. The 3D surface models are available in the article’s online version for viewing and downloading using the reader’s software of choice. These 3D graphic displays are represented in the print version as 2D snapshots. Overlays and color-coded distance maps can be displayed using the reader’s software of choice, allowing graphic assessment of the location and direction of changes or morphologic differences relative to the structure of reference. The interpretation of 3D overlays and quantitative color-coded maps requires basic knowledge of 3D image analysis. Conclusions When submitting manuscripts, authors can

  2. Hip dysplasia, pelvic obliquity, and scoliosis in cerebral palsy: a qualitative analysis using 3D CT reconstruction

    NASA Astrophysics Data System (ADS)

    Russ, Mark D.; Abel, Mark F.

    1998-06-01

    Five patients with cerebral palsy, hip dysplasia, pelvic obliquity, and scoliosis were evaluated retrospectively using three dimensional computed tomography (3DCT) scans of the proximal femur, pelvis, and lumbar spine to qualitatively evaluate their individual deformities by measuring a number of anatomical landmarks. Three dimensional reconstructions of the data were visualized, analyzed, and then manipulated interactively to perform simulated osteotomies of the proximal femur and pelvis to achieve surgical correction of the hip dysplasia. Severe deformity can occur in spastic cerebral palsy, with serious consequences for the quality of life of the affected individuals and their families. Controversy exists regarding the type, timing and efficacy of surgical intervention for correction of hip dysplasia in this population. Other authors have suggested 3DCT studies are required to accurately analyze acetabular deficiency, and that this data allows for more accurate planning of reconstructive surgery. It is suggested here that interactive manipulation of the data to simulate the proposed surgery is a clinically useful extension of the analysis process and should also be considered as an essential part of the pre-operative planning to assure that the appropriate procedure is chosen. The surgical simulation may reduce operative time and improve surgical correction of the deformity.

  3. Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data

    NASA Astrophysics Data System (ADS)

    Schäfer, D.; Lin, M.; Rao, P. P.; Loffroy, R.; Liapi, E.; Noordhoek, N.; Eshuis, P.; Radaelli, A.; Grass, M.; Geschwind, J.-F. H.

    2012-03-01

    C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

  4. WE-D-18A-04: How Iterative Reconstruction Algorithms Affect the MTFs of Variable-Contrast Targets in CT Images

    SciTech Connect

    Dodge, C.T.; Rong, J.; Dodge, C.W.

    2014-06-15

    Purpose: To determine how filtered back-projection (FBP), adaptive statistical (ASiR), and model based (MBIR) iterative reconstruction algorithms affect the measured modulation transfer functions (MTFs) of variable-contrast targets over a wide ran