Relevant bibliographies by topics / CT Coronary Angiography (CCTA)

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  1. Journal articles
  2. Dissertations / Theses
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  4. Book chapters
  5. Conference papers

Academic literature on the topic 'CT Coronary Angiography (CCTA)'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "CT Coronary Angiography (CCTA)"

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Chow, Alyssa L. S., Saad D. Alhassani, Andrew M. Crean, and Gary R. Small. "Coronary CT Angiography Guided Medical Therapy in Subclinical Atherosclerosis." Journal of Clinical Medicine 10, no. 4 (February 7, 2021): 625. http://dx.doi.org/10.3390/jcm10040625.

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The goals of primary prevention in coronary atherosclerosis are to avoid sudden cardiac death, myocardial infarction or the need for revascularization procedures. Successful prevention will rely on accurate identification, effective therapy and monitoring of those at risk. Identification and potential monitoring can be achieved using cardiac computed tomography (CT). Cardiac CT can determine coronary artery calcification (CAC), a useful surrogate of coronary atherosclerosis burden. Cardiac CT can also assess coronary CT angiography (CCTA). CCTA can identify arterial lumen narrowing and highlight mural atherosclerosis hitherto hidden from other anatomical approaches. Herein we consider the role of CCTA and CAC-scoring in subclinical atherosclerosis. We explore the use of these modalities in screening and discuss data that has used CCTA for guiding primary prevention. We examine therapeutic trials using CCTA to determine the effects of plaque-modifying therapies. Finally, we address the role of CCTA and CAC to guide therapy as defined in current primary prevention documents. CCTA has emerged as an essential tool in the detection and management of clinical coronary artery disease. To date, its role in subclinical atherosclerosis is less well defined, yet with modern CT scanners and continued pharmacotherapy development, CCTA is likely to achieve a more prominent place in the primary prevention of coronary atherosclerosis.
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Sun, Zhonghua, and Lei Xu. "Coronary CT Angiography in the Quantitative Assessment of Coronary Plaques." BioMed Research International 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/346380.

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Coronary computed tomography angiography (CCTA) has been recently evaluated for its ability to assess coronary plaque characteristics, including plaque composition. Identification of the relationship between plaque composition by CCTA and patient clinical presentations may provide insight into the pathophysiology of coronary artery plaque, thus assisting identification of vulnerable plaques which are associated with the development of acute coronary syndrome. CCTA-generated 3D visualizations allow evaluation of both coronary lesions and lumen changes, which are considered to enhance the diagnostic performance of CCTA. The purpose of this review is to discuss the recent developments that have occurred in the field of CCTA with regard to its diagnostic accuracy in the quantitative assessment of coronary plaques, with a focus on the characterization of plaque components and identification of vulnerable plaques.
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Nakanishi, Rine, and Matthew J. Budoff. "A New Approach in Risk Stratification by Coronary CT Angiography." Scientifica 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/278039.

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For a decade, coronary computed tomographic angiography (CCTA) has been used as a promising noninvasive modality for the assessment of coronary artery disease (CAD) as well as cardiovascular risks. CCTA can provide more information incorporating the presence, extent, and severity of CAD; coronary plaque burden; and characteristics that highly correlate with those on invasive coronary angiography. Moreover, recent techniques of CCTA allow assessing hemodynamic significance of CAD. CCTA may be potentially used as a substitute for other invasive or noninvasive modalities. This review summarizes risk stratification by anatomical and hemodynamic information of CAD, coronary plaque characteristics, and burden observed on CCTA.
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Misaka, Tomofumi, Yuki Sugitani, Nobuyuki Asato, Yuko Matsukubo, Masanobu Uemura, Ryuichiro Ashikaga, and Takayuki Ishida. "Coronary artery to aortic luminal attenuation ratio in coronary CT angiography for the diagnosis of haemodynamically significant coronary artery stenosis." British Journal of Radiology 93, no. 1105 (January 2020): 20190003. http://dx.doi.org/10.1259/bjr.20190003.

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Objective: This study aimed to assess and compare the diagnostic performance of the coronary artery to aortic luminal attenuation ratio (CAR), transluminal attenuation gradient (TAG), and corrected coronary opacification (CCO) difference on coronary CT angiography (cCTA) for detecting haemodynamically significant coronary artery stenosis. Methods: 33 patients who underwent cCTA, gated SPECT myocardial perfusion imaging (MPI), and invasive coronary angiography within 3 months were included in this retrospective study. The degree of coronary stenosis on cCTA was visually assessed in all patients. Additionally, CAR, TAG, and CCO difference were analyzed and calculated in all patients. Haemodynamically significant coronary stenosis was defined as a vessel with ≥50% luminal stenosis on invasive coronary angiography and an associated abnormal perfusion defect on MPI in the same territory. Diagnostic performance was assessed on a per-vessel basis by the area under the receiver operating characteristic (ROC) curve (AUC). Results: Among 99 vessels, 12 were excluded and the remaining 87 were analyzed. 17 (19.5%) vessels were determined as haemodynamically significant coronary artery stenosis. On ROC analysis, the AUC was 0.71 for cCTA, 0.80 for CAR, 0.61 for TAG, 0.74 for CCO, 0.87 for combined CAR and cCTA, 0.77 for combined TAG and cCTA, and 0.75 for combined CCO and cCTA. The AUC for combined CAR and cCTA was significantly greater compared with cCTA alone (p < 0.01). Conclusion: Non-invasive CAR derived from 64-detector row CT was feasible and might be helpful for the detection of haemodynamically significant coronary artery stenosis. Still, further investigations such as intra- and inter-reader correlation, evaluation of larger numbers in different settings, and time efficiency are required for applying CAR in various situations. Advances in knowledge: CAR could be used as novel noninvasive technique to detect haemodynamically significant coronary artery stenosis.
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Xu, Lei, Zhonghua Sun, and Zhanming Fan. "Noninvasive Physiologic Assessment of Coronary Stenoses Using Cardiac CT." BioMed Research International 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/435737.

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Coronary CT angiography (CCTA) has become an important noninvasive imaging modality in the diagnosis of coronary artery disease (CAD). CCTA enables accurate evaluation of coronary artery stenosis. However, CCTA provides limited information on the physiological significance of stenotic lesions. A noninvasive “one-stop-shop” diagnostic test that can provide both anatomical significance and functional significance of stenotic lesions would be beneficial in the diagnosis and management of CAD. Recently, with the introduction of novel techniques, such as myocardial CT perfusion, CT-derived fractional flow reserve (FFRCT), and transluminal attenuation gradient (TAG), CCTA has emerged as a noninvasive method for the assessment of both anatomy of coronary lesions and its physiological consequences during a single study. This review provides an overview of the current status of new CT techniques for the physiologic assessments of CAD.
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Amin, Sagar B., and Arthur E. Stillman. "SCOT-HEART trial: reshuffling our approach to stable ischemic heart disease." British Journal of Radiology 93, no. 1113 (September 1, 2020): 20190763. http://dx.doi.org/10.1259/bjr.20190763.

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The role of diagnostic testing in triaging patients with stable ischemic heart disease continues to evolve towards recognizing the benefits of coronary CT angiography (CCTA) over functional testing. The SCOT-HEART (Scottish Computed Tomography of the HEART) trial highlights this paradigm shift finding a significant reduction of death from coronary heart disease or non-fatal myocardial infarction without a significant increased rate of invasive coronary angiography over a 5 year follow-up period when implementing CCTA with standard care vs standard care alone. The better negative predictive value and ability to identify nonobstructive coronary artery disease to optimize medical therapy highlight the benefits of a CCTA first strategy. With the advent of noninvasive fractional flow reserve (FFR) and widespread availability and ease of CT, CCTA continues to establish itself as a pivotal diagnostic exam for patients with stable ischemic heart disease. In this commentary, we review the SCOT-HEART trial and its impact on CCTA for patients with stable ischemic heart disease.
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Cyrus, Tillmann, Robert J. Gropler, and Pamela K. Woodard. "Coronary CT angiography (CCTA) and advances in CT plaque imaging." Journal of Nuclear Cardiology 16, no. 3 (April 28, 2009): 466–73. http://dx.doi.org/10.1007/s12350-009-9084-y.

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Rottländer, Dennis, Martin Saal, Hubertus Degen, Miriel Gödde, Marc Horlitz, and Michael Haude. "Diagnostic role of coronary CT angiography in paroxysmal or first diagnosed atrial fibrillation." Open Heart 8, no. 1 (May 2021): e001638. http://dx.doi.org/10.1136/openhrt-2021-001638.

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ObjectivesThe presence of coronary artery disease (CAD) in patients hospitalised with paroxysmal or first diagnosed atrial fibrillation (AF) has major implications for antithrombotic therapy and cardiovascular event rate. Coronary CT angiography (CCTA) is a feasible tool to identify patients with concealed CAD. We aimed to evaluate the diagnostic role of early CCTA in patients hospitalised with paroxysmal or first diagnosed AF.MethodsIn a 5-year single-centre retrospective analysis, 566 patients with paroxysmal or first diagnosed AF who underwent CCTA were enrolled to investigate the presence of CAD.ResultsIn patients with paroxysmal or first diagnosed AF, CCTA revealed CAD (coronary artery stenosis ≥50%) in 39.2%. Cardiac catheterisation was performed in 31.6%, confirming CAD in 13.1% of all patients. In 8.0% percutaneous coronary intervention and in 0.5% coronary artery bypass grafting was performed. In patients with paroxysmal or first diagnosed AF: (1) angina pectoris per se does not predict CAD; (2) multivariable regression analysis revealed age, male sex and diabetes as risk factors for CAD in AF; (3) Framingham Risk Score for coronary heart disease and CHA2DS2-VASc-Score were relevant risk scores of CAD and (4) the classification of Coronary Artery Calcium score reference values according to the Multi-Ethnic Study of Atherosclerosis was a predictor of CAD.ConclusionPatients with paroxysmal or first diagnosed AF are at risk for CAD, while CCTA is a feasible diagnostic tool for CAD. We recommend to integrate CT calcium scoring and CCTA into the diagnostic workup of patients with new-onset or paroxysmal AF.
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Deng, Fuquan, Changjun Tie, Yingting Zeng, Yanbin Shi, Huiying Wu, Yu Wu, Dong Liang, et al. "Correcting motion artifacts in coronary computed tomography angiography images using a dual-zone cycle generative adversarial network." Journal of X-Ray Science and Technology 29, no. 4 (July 27, 2021): 577–95. http://dx.doi.org/10.3233/xst-210841.

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BACKGROUND: Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality to detect and diagnose coronary artery disease. Due to the limitations of equipment and the patient’s physiological condition, some CCTA images collected by 64-slice spiral computed tomography (CT) have motion artifacts in the right coronary artery, left circumflex coronary artery and other positions. OBJECTIVE: To perform coronary artery motion artifact correction on clinical CCTA images collected by Siemens 64-slice spiral CT and evaluate the artifact correction method. METHODS: We propose a novel method based on the generative adversarial network (GAN) to correct artifacts of CCTA clinical images. We use CCTA clinical images collected by 64-slice spiral CT as the original dataset. Pairs of regions of interest (ROIs) cropped from original dataset or images with and without motion artifacts are used to train the dual-zone GAN. When predicting the CCTA images, the network inputs only the clinical images with motion artifacts. RESULTS: Experiments show that this network effectively corrects CCTA motion artifacts. Regardless of ROIs or images, the peak signal to noise ratio (PSNR), structural similarity (SSIM), mean square error (MSE) and mean absolute error (MAE) of the generated images are greatly improved compared to those of the input data. In addition, based on scores from physicians, the average score for the coronary artery artifact correction of the output images is higher. CONCLUSIONS: This study demonstrates that the dual-zone GAN has the excellent ability to correct motion artifacts in the coronary arteries and maintain the overall characteristics of CCTA clinical images.
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Gohmann, Robin F., Philipp Lauten, Patrick Seitz, Christian Krieghoff, Christian Lücke, Sebastian Gottschling, Meinhard Mende, et al. "Combined Coronary CT-Angiography and TAVI-Planning: A Contrast-Neutral Routine Approach for Ruling-Out Significant Coronary Artery Disease." Journal of Clinical Medicine 9, no. 6 (May 27, 2020): 1623. http://dx.doi.org/10.3390/jcm9061623.

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Background: Significant coronary artery disease (CAD) is a common finding in patients undergoing transcatheter aortic valve implantation (TAVI). Assessment of CAD prior to TAVI is recommended by current guidelines and is mainly performed via invasive coronary angiography (ICA). In this study we analyzed the ability of coronary CT-angiography (cCTA) to rule out significant CAD (stenosis ≥ 50%) during routine pre-TAVI evaluation in patients with high pre-test probability for CAD. Methods: In total, 460 consecutive patients undergoing pre-TAVI CT (mean age 79.6 ± 7.4 years) were included. All patients were examined with a retrospectively ECG-gated CT-scan of the heart, followed by a high-pitch-scan of the vascular access route utilizing a single intravenous bolus of 70 mL iodinated contrast medium. Images were evaluated for image quality, calcifications, and significant CAD; CT-examinations in which CAD could not be ruled out were defined as positive (CAD+). Routinely, patients received ICA (388/460; 84.3%; Group A), which was omitted if renal function was impaired and CAD was ruled out on cCTA (Group B). Following TAVI, clinical events were documented during the hospital stay. Results: cCTA was negative for CAD in 40.2% (188/460). Sensitivity, specificity, PPV, and NPV in Group A were 97.8%, 45.2%, 49.6%, and 97.4%, respectively. Median coronary artery calcium score (CAC) was higher in CAD+-patients but did not have predictive value for correct classification of patients with cCTA. There were no significant differences in clinical events between Group A and B. Conclusion: cCTA can be incorporated into pre-TAVI CT-evaluation with no need for additional contrast medium. cCTA may exclude significant CAD in a relatively high percentage of these high-risk patients. Thereby, cCTA may have the potential to reduce the need for ICA and total amount of contrast medium applied, possibly making pre-procedural evaluation for TAVI safer and faster.
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Dissertations / Theses on the topic "CT Coronary Angiography (CCTA)"

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Graber, Taylor. "Imaging for Chest Pain Assessment: An Algorithmic Approach Using Noninvasive Modalities to Define Medical vs. Interventional Treatment." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/623439.

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A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.
To analyze the roles of CCTA, MPI, and CC to formulate a sequential clinical algorithm to use in patients with chest pain, risk factors for CAD, and an abnormal EKG. The goals of the study are to streamline and refine workup, to decrease radiation exposure to patients, and to contain costs. 39 patients underwent CCTA, MPI, and CC within 30 months of each other. CCTA was used to categorize mild, moderate, or severe CAD. MPI used SSS, SDS, TID, and formal reading to define mild, moderate, or severe physiologic ischemia. CC and coronary intervention cine films were analyzed to define and treat anatomical CAD medically or by intervention. Results: There was strong correlation between CCTA, CC, and treatment type (p<0.0001). CCTA was able to stratify all patients with mild or severe ischemia to appropriate treatment groups, and to reduce the need for MPI. With moderate ischemia from CCTA, the additional use of MPI could have reduced the need for 16/18 (89%) patients who underwent CC to undergo further testing. No patients with mild or moderate CAD by CCTA, followed by mild to moderate physiologic ischemia by MPI, needed CC or intervention. 37/39 patients (95%) could have avoided one or more tests using our algorithm. CCTA followed by MPI may be used in symptomatic patients with risk factors for CAD and an abnormal EKG to stratify mild and moderate CAD, and to thereby avoid cardiac catheterization. Our algorithm could lead to savings in healthcare expenditures, save patients from unnecessary invasive procedures, decrease radiation exposure, and total cost.
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Mieghem, C. A. G. van. "CT coronary angiography: validation and clinical implementation." [S.l.] : Rotterdam : [The Author] ; Erasmus University [Host], 2009. http://hdl.handle.net/1765/14640.

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Silva, Samuel de Sousa. "Left ventricle functional analysis from coronary CT angiography." Doctoral thesis, Universidade de Aveiro, 2012. http://hdl.handle.net/10773/8077.

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Doutoramento em Engenharia Informática
Coronary CT angiography is widely used in clinical practice for the assessment of coronary artery disease. Several studies have shown that the same exam can also be used to assess left ventricle (LV) function. LV function is usually evaluated using just the data from end-systolic and end-diastolic phases even though coronary CT angiography (CTA) provides data concerning multiple cardiac phases, along the cardiac cycle. This unused wealth of data, mostly due to its complexity and the lack of proper tools, has still to be explored in order to assess if further insight is possible regarding regional LV functional analysis. Furthermore, different parameters can be computed to characterize LV function and while some are well known by clinicians others still need to be evaluated concerning their value in clinical scenarios. The work presented in this thesis covers two steps towards extended use of CTA data: LV segmentation and functional analysis. A new semi-automatic segmentation method is presented to obtain LV data for all cardiac phases available in a CTA exam and a 3D editing tool was designed to allow users to fine tune the segmentations. Regarding segmentation evaluation, a methodology is proposed in order to help choose the similarity metrics to be used to compare segmentations. This methodology allows the detection of redundant measures that can be discarded. The evaluation was performed with the help of three experienced radiographers yielding low intraand inter-observer variability. In order to allow exploring the segmented data, several parameters characterizing global and regional LV function are computed for the available cardiac phases. The data thus obtained is shown using a set of visualizations allowing synchronized visual exploration. The main purpose is to provide means for clinicians to explore the data and gather insight over their meaning, as well as their correlation with each other and with diagnosis outcomes. Finally, an interactive method is proposed to help clinicians assess myocardial perfusion by providing automatic assignment of lesions, detected by clinicians, to a myocardial segment. This new approach has obtained positive feedback from clinicians and is not only an improvement over their current assessment method but also an important first step towards systematic validation of automatic myocardial perfusion assessment measures.
A angiografia coronária por TC (angio-TC) é prática clínica corrente para a avaliação de doença coronária. Alguns estudos mostram que é também possível utilizar o exame de angio-TC para avaliar a função do ventrículo esquerdo (VE). A função ventricular esquerda (FVE) é normalmente avaliada considerando as fases de fim de sístole e de fim de diástole, apesar de a angio-TC proporcionar dados relativos a diferentes fases distribuídas ao longo do ciclo cardíaco. Estes dados não considerados, devido à sua complexidade e à falta de ferramentas apropriadas para o efeito, têm ainda de ser explorados para que se perceba se possibilitam uma melhor compreensão da FVE. Para além disso, podem ser calculados diferentes parâmetros para caracterizar a FVE e, enquanto alguns são bem conhecidos dos médicos, outros requerem ainda uma avaliação do seu valor clínico. No âmbito de uma utilização alargada dos dados proporcionados pelos angio- TC, este trabalho apresenta contributos ao nível da segmentação do VE e da sua análise funcional. É proposto um método semi-automático para a segmentação do VE de forma a obter dados para as diferentes fases cardíacas presentes no exame de angio- TC. Foi também desenvolvida uma ferramenta de edição 3D que permite aos utilizadores a correcção das segmentações assim obtidas. Para a avaliação do método de segmentação apresentado foi proposta uma metodologia que permite a detecção de medidas de similaridade redundantes, a usar no âmbito da avaliação para comparação entre segmentações, para que tais medidas redundantes possam ser descartadas. A avaliação foi executada com a colaboração de três técnicos de radiologia experientes, tendo-se verificado uma baixa variabilidade intra- e inter-observador. De forma a permitir explorar os dados segmentados, foram calculados vários parâmetros para caracterização global e regional da FVE, para as diversas fases cardíacas disponíveis. Os resultados assim obtidos são apresentados usando um conjunto de visualizações que permitem uma exploração visual sincronizada dos mesmos. O principal objectivo é proporcionar ao médico a exploração dos resultados obtidos para os diferentes parâmetros, de modo a que este tenha uma compreensão acrescida sobre o seu significado clínico, assim como sobre a correlação existente entre diferentes parâmetros e entre estes e o diagnóstico. Finalmente, foi proposto um método interactivo para ajudar os médicos durante a avaliação da perfusão do miocárdio, que atribui automaticamente as lesões detectadas pelo médico ao respectivo segmento do miocárdio. Este novo método obteve uma boa receptividade e constitui não só uma melhoria em relação ao método tradicional mas é também um primeiro passo para a validação sistemática de medidas automáticas da perfusão do miocárdio.
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Feger, Sarah [Verfasser]. "Patient satisfaction with coronary CT angiography, myocardial CT perfusion, myocardial perfusion MRI, SPECT myocardial perfusion imaging and conventional coronary angiography / Sarah Feger." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2016. http://d-nb.info/1102196932/34.

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Wang, Chunliang. "Computer Assisted Coronary CT Angiography Analysis : Disease-centered Software Development." Licentiate thesis, Linköping University, Linköping University, Radiology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-17783.

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The substantial advances of coronary CTA have resulted in a boost of use of this new technique in the last several years, which brings a big challenge to radiologists by the increasing number of exams and the large amount of data for each patient. The main goal of this study was to develop a computer tool to facilitate coronary CTA analysis by combining knowledge of medicine and image processing.Firstly, a competing fuzzy connectedness tree algorithm was developed to segment the coronary arteries and extract centerlines for each branch. The new algorithm, which is an extension of the “virtual contrast injection” method, preserves the low density soft tissue around the coronary, which reduces the possibility of introducing false positive stenoses during segmentation.Secondly, this algorithm was implemented in open source software in which multiple visualization techniques were integrated into an intuitive user interface to facilitate user interaction and provide good over¬views of the processing results. Considerable efforts were put on optimizing the computa¬tional speed of the algorithm to meet the clinical requirements.Thirdly, an automatic seeding method, that can automatically remove rib cage and recognize the aortic root, was introduced into the interactive segmentation workflow to further minimize the requirement of user interactivity during post-processing. The automatic procedure is carried out right after the images are received, which saves users time after they open the data. Vessel enhance¬ment and quantitative 2D vessel contour analysis are also included in this new version of the software. In our preliminary experience, visually accurate segmentation results of major branches have been achieved in 74 cases (42 cases reported in paper II and 32 cases in paper III) using our software with limited user interaction. On 128 branches of 32 patients, the average overlap between the centerline created in our software and the manually created reference standard was 96.0%. The average distance between them was 0.38 mm, lower than the mean voxel size. The automatic procedure ran for 3-5 min as a single-thread application in the background. Interactive processing took 3 min in average with the latest version of software. In conclusion, the presented software provides fast and automatic coron¬ary artery segmentation and visualization. The accuracy of the centerline tracking was found to be acceptable when compared to manually created centerlines.

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Wick, Carson A. "Detection and prediction of cardiac quiescence for computed tomography coronary angiography." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/52242.

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The objective of this work is to improve the diagnostic quality and reduce the radiation dose of computed tomography coronary angiography (CTCA) imaging by developing gating techniques based on signals derived from cardiac motion, rather than the currently used electrocardiogram (ECG), to more reliably trigger data acquisition during periods of cardiac quiescence. Because the ECG is an indication of electrical activity, it is a surrogate marker of the mechanical state of the heart. Therefore, gating based on a signal derived directly from cardiac motion using either echocardiography or seismocardiography (SCG) should prove better at detecting and predicting periods of cardiac quiescence. Improved gating would permit the use of CTCA in more instances to either replace or determine the necessity of invasive and expensive CCAs. This work presents novel methods for detecting and predicting cardiac quiescence. Quiescence is detected as periods of minimal velocity from echocardiography, computed tomography (CT), and SCG. Identified quiescent periods are used to develop and evaluate techniques for predicting cardiac quiescence using echocardiography and SCG. Both echocardiography and SCG are shown to be more accurate for predicting quiescent periods than ECG. Additionally, the average motion during quiescent periods predicted by echocardiography and SCG is shown to be lower than those predicted using only ECG. Lastly, cardiac CT reconstructions from quiescent phases predicted by a commercial CT scanner were compared to the optimal quiescent phases calculated using the CT quiescence detection methods presented in this work. The diagnostic quality of the reconstructions from the optimal phases was found to be higher than that of the phases predicted by the CT scanner, suggesting that there is the potential for marked improvement in CTCA performance through more accurate cardiac gating.
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Jawaid, M. M. "Detection, localization and quantification of non-calcified coronary plaques in contrast enhanced CT angiography." Thesis, City, University of London, 2017. http://openaccess.city.ac.uk/19157/.

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State-of-the-art imaging equipment has increased clinician's ability to make non-invasive diagnoses of coronary heart disease (CHD); however, high volumes of imaging data make manual abnormality detection cumbersome in practice. In addition, the interpretation of CTA heavily relies upon the previous knowledge of the clinician. These limitations have driven an intense research in the context of automated solutions for fast, reliable and accurate diagnosis. Accordingly, in this thesis, we present an automated framework for detection, localization and quantification of the non-calcified coronary plaques in cardiac computed tomography angiography (CTA). The first contribution of the thesis is a coronary segmentation algorithm that is adaptive to the contrast agent and employs a hybrid energy incorporating local and global image statistics in a segmentation framework using partial differential equations (PDEs). Accordingly, we illustrated with the help of experimental evidence that a volume-specific intensity threshold leads to an improved segmentation in CTA. In the subsequent step, we employed a hybrid region-based energy for improved segmentation in CTA imagery. The hybrid energy couples an intensity-based local term with an efficient discontinuity-based global model of the image for optimal segmentation. The proposed method is less sensitive to the local optima problem and helps in reducing false positives, as well as it allows a certain degree of freedom for the initialization. Moreover, we employed an auto-correction feature for improved segmentation, as an auto-corrected mask captures the emerging peripheries of the coronary tree during the curve evolution. The effectiveness of the proposed model is demonstrated with the help of both qualitative and quantitative results, with a mean accuracy of 80% across the CTA dataset. The capability to address the variations in initial mask and localization radii simultaneously, makes our algorithm a feasible choice for coronary segmentation. The second contribution of the thesis is an automatic approach to analyse the segmented coronary tree for the presence of non-calcified plaques. The specific focus of this work is detection of non-calcified plaques in CTA, as intensity overlap between blood, fat and non-calcified plaques make the detection challenging. Non-calcified plaques are identified based on mean radial profiles that average the image intensities in concentric rings around the vessel centreline. Subsequently, an SVM classifier is applied to differentiate the abnormal coronary segments from normal ones. A total of 32 CTA volumes have been analysed and a detection accuracy of 88.4% with respect to the manual expert has been achieved. For plaque-affected segments, we further proposed a derivative-based method to localize the position and length of the plaque inside the segment. The plaque localization accuracy has been around 83.2%. Moreover, the proposed model has been tested on three different CTA datasets and has produced consistent results, demonstrating its reproducibility for generic CTA data. The final contribution of the thesis is a method to segment and quantify the non-calcified plaque. After evaluating the vessel wall thickness, posterior probability based voxel classification has been performed to quantify the lumen and plaque, respectively. Both qualitative and quantitative results demonstrate that the proposed model shows a good agreement with three independent experts. To optimize the processing time, we employed sparse field method in a level-set based active contour evolution.
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Melki, Imen. "Towards an automated framework for coronary lesions detection and quantification in cardiac CT angiography." Thesis, Paris Est, 2015. http://www.theses.fr/2015PESC1022/document.

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Les maladies coronariennes constituent l'ensemble des troubles affectant les artères coronaires. Elles sont la première cause mondiale de mortalité. Par conséquent, la détection précoce de ces maladies en utilisant des techniques peu invasives fournit un meilleur résultat thérapeutique, et permet de réduire les coûts et les risques liés à une approche interventionniste. Des études récentes ont montré que la tomodensitométrie peut être utilisée comme une alternative non invasive et fiable pour localiser et quantifier ces lésions. Cependant, l'analyse de ces examens, basée sur l'inspection des sections du vaisseau, reste une tâche longue et fastidieuse. Une haute précision est nécessaire, et donc seulement les cliniciens hautement expérimentés sont en mesure d'analyser et d'interpréter de telles données pour établir un diagnostic. Les outils informatiques sont essentiels pour réduire les temps de traitement et assurer la qualité du diagnostic. L'objectif de cette thèse est de fournir des outils automatisés de traitement d'angiographie CT, pour la visualisation et l'analyse des artères coronaires d'une manière non invasive. Ces outils permettent aux pathologistes de diagnostiquer et évaluer efficacement les risques associés aux maladies cardio-vasculaires tout en améliorant la qualité de l'évaluation d'un niveau purement qualitatif à un niveau quantitatif. Le premier objectif de ce travail est de concevoir, analyser et valider un ensemble d'algorithmes automatisés utiles pour la détection et la quantification de sténoses des artères coronaires. Nous proposons un nombre de techniques couvrant les différentes étapes de la chaîne de traitement vers une analyse entièrement automatisée des artères coronaires. Premièrement, nous présentons un algorithme dédié à l'extraction du cœur. L'approche extrait le cœur comme un seul objet, qui peut être utilisé comme un masque d'entrée pour l'extraction automatisée des coronaires. Ce travail élimine l'étape longue et fastidieuse de la segmentation manuelle du cœur et offre rapidement une vue claire des coronaires. Cette approche utilise un modèle géométrique du cœur ajusté aux données de l'image. La validation de l'approche sur un ensemble de 133 examens montre l'efficacité et la précision de cette approche. Deuxièmement, nous nous sommes intéressés au problème de la segmentation des coronaires. Dans ce contexte, nous avons conçu une nouvelle approche pour l'extraction de ces vaisseaux, qui combine ouvertures par chemin robustes et filtrage sur l'arbre des composantes connexes. L'approche a montré des résultats prometteurs sur un ensemble de 11 examens CT. Pour une détection et quantification robuste de la sténose, une segmentation précise de la lumière du vaisseau est cruciale. Par conséquent, nous avons consacré une partie de notre travail à l'amélioration de l'étape de segmentation de la lumière, basée sur des statistiques propres au vaisseau. La validation avec l'outil d'évaluation en ligne du challenge de Rotterdam sur la segmentation des coronaires, a montré que cette approche présente les mêmes performances que les techniques de l'état de l'art. Enfin, le cœur de cette thèse est consacré à la problématique de la détection et la quantification des sténoses. Deux approches sont conçues et évaluées en utilisant l'outil d'évaluation en ligne de l'équipe de Rotterdam. La première approche se base sur l'utilisation de la segmentation de la lumière avec des caractéristiques géométriques et d'intensité pour extraire les sténoses coronaires. La seconde utilise une approche basée sur l'apprentissage. Durant cette thèse, un prototype pour l'analyse automatisée des artères coronaires et la détection et quantification des sténoses a été développé. L'évaluation qualitative et quantitative sur différents bases d'examens cardiaques montre qu'il atteint le niveau de performances requis pour une utilisation clinique
Coronary heart diseases are the group of disorders that affect the coronary artery vessels. They are the world's leading cause of mortality. Therefore, early detection of these diseases using less invasive techniques provides better therapeutic outcome, as well as reduces costs and risks, compared to an interventionist approach. Recent studies showed that X-ray computed tomography (CT) may be used as an alternative to accurately locate and grade heart lesions in a non invasive way. However, analysis of cardiac CT exam for coronaries lesions inspection remains a tedious and time consuming task, as it is based on the manual analysis of the vessel cross sections. High accuracy is required, and thus only highly experienced clinicians are able to analyze and interpret the data for diagnosis. Computerized tools are critical to reduce processing time and ensure quality of diagnostics. The goal of this thesis is to provide automated coronaries analysis tools to help in non-invasive CT angiography examination. Such tools allow pathologists to efficiently diagnose and evaluate risks associated with CVDs, and to raise the quality of the assessment from a purely qualitative level to a quantitative level. The first objective of our work is to design, analyze and validate a set of automated algorithms for coronary arteries analysis with the final purpose of automated stenoses detection and quantification. We propose different algorithms covering different processing steps towards a fully automated analysis of the coronary arteries. Our contribution covers the three major blocks of the whole processing chain and deals with different image processing fields. First, we present an algorithm dedicated to heart volume extraction. The approach extracts the heart as one single object that can be used as an input masque for automated coronary arteries segmentation. This work eliminates the tedious and time consuming step of manual removing obscuring structures around the heart (lungs, ribs, sternum, liver...) and quickly provides a clear and well defined view of the coronaries. This approach uses a geometric model of the heart that is fitted and adapted to the image data. Quantitative and qualitative analysis of results obtained on a 114 exam database shows the efficiency and the accuracy of this approach. Second, we were interested to the problem of coronary arteries enhancement and segmentation. In this context, we first designed a novel approach for coronaries enhancement that combines robust path openings and component tree filtering. The approach showed promising results on a set of 11 CT exam compared to a Hessian based approach. For a robust stenoses detection and quantification, a precise and accurate lumen segmentation is crucial. Therefore, we have dedicated a part of our work to the improvement of lumen segmentation step based on vessel statistics. Validation on the Rotterdam Coronary Challenge showed that this approach provides state of the art performances. Finally, the major core of this thesis is dedicated to the issue of stenosis detection and quantification. Two different approaches are designed and evaluated using the Rotterdam online evaluation framework. The first approach get uses of the lumen segmentation with some geometric and intensity features to extract the coronary stenosis. The second is using a learning based approach for stenosis detection and stenosis. The second approach outperforms some of the state of the art works with reference to some metrics. This thesis results in a prototype for automated coronary arteries analysis and stenosis detection and quantification that meets the level of required performances for a clinical use. The prototype was qualitatively and quantitatively validated on different sets of cardiac CT exams
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Wang, Yin. "Blood vessel segmentation and shape analysis for quantification of coronary artery stenosis in CT angiography." Thesis, City University London, 2011. http://openaccess.city.ac.uk/1186/.

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This thesis presents an automated framework for quantitative vascular shape analysis of the coronary arteries, which constitutes an important and fundamental component of an automated image-based diagnostic system. Firstly, an automated vessel segmentation algorithm is developed to extract the coronary arteries based on the framework of active contours. Both global and local intensity statistics are utilised in the energy functional calculation, which allows for dealing with non-uniform brightness conditions, while evolving the contour towards to the desired boundaries without being trapped in local minima. To suppress kissing vessel artifacts, a slice-by-slice correction scheme, based on multiple regions competition, is proposed to identify and track the kissing vessels throughout the transaxial images of the CTA data. Based on the resulting segmentation, we then present a dedicated algorithm to estimate the geometric parameters of the extracted arteries, with focus on vessel bifurcations. In particular, the centreline and associated reference surface of the coronary arteries, in the vicinity of arterial bifurcations, are determined by registering an elliptical cross sectional tube to the desired constituent branch. The registration problem is solved by a hybrid optimisation method, combining local greedy search and dynamic programming, which ensures the global optimality of the solution and permits the incorporation of any hard constraints posed to the tube model within a natural and direct framework. In contrast with conventional volume domain methods, this technique works directly on the mesh domain, thus alleviating the need for image upsampling. The performance of the proposed framework, in terms of efficiency and accuracy, is demonstrated on both synthetic and clinical image data. Experimental results have shown that our techniques are capable of extracting the major branches of the coronary arteries and estimating the related geometric parameters (i.e., the centreline and the reference surface) with a high degree of agreement to those obtained through manual delineation. Particularly, all of the major branches of coronary arteries are successfully detected by the proposed technique, with a voxel-wise error at 0.73 voxels to the manually delineated ground truth data. Through the application of the slice-by-slice correction scheme, the false positive metric, for those coronary segments affected by kissing vessel artifacts, reduces from 294% to 22.5%. In terms of the capability of the presented framework in defining the location of centrelines across vessel bifurcations, the mean square errors (MSE) of the resulting centreline, with respect to the ground truth data, is reduced by an average of 62.3%, when compared with initial estimation obtained using a topological thinning based algorithm.
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Dick, Eric Timothy. "A survey of CT phantom considerations for the study of blooming artifacts as observed in CT coronary angiography studies a preliminary study /." Cincinnati, Ohio : University of Cincinnati, 2008. http://www.ohiolink.edu/etd/view.cgi?acc_num=ucin1205313085.

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Thesis (M.S. of Medical Physics)--University of Cincinnati, 2008.
Advisor: Lisa Lemen PhD. Title from electronic thesis title page (viewed May 12, 2008). Includes abstract. Keywords: blooming; computed tomography; artifact; CT; beam hardening; partial volume averaging;cone beam. Includes bibliographical references.
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Books on the topic "CT Coronary Angiography (CCTA)"

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service), SpringerLink (Online, ed. Coronary CT Angiography. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

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R, Mollet Nico, and Hoffmann Udo, eds. CT coronary angiography: An atlas of investigation and diagnosis. Oxford: Clinical Pub., 2011.

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Massimo, Fioranelli, Dowe David A, and SpringerLink (Online service), eds. CT Evaluation of Coronary Artery Disease. Milano: Springer Milan, 2009.

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Buechel, Ronny R., and Aju P. Pazhenkottil. Basic principles and technological state of the art: hybrid imaging. Edited by Philipp Kaufmann. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198784906.003.0121.

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The core principle of hybrid imaging is based on the fact that it provides information beyond that achievable with either data set alone. This is attained through the combination and fusion of two datasets by which both modalities synergistically contribute to image information. Hybrid imaging is, thus, more powerful than the sum of its parts, yielding improved sensitivity and specificity. While datasets for integration may be obtained by a variety of imaging modalities, its merits are intuitively best exploited when combining anatomical and functional imaging, particularly in the setting of evaluation of coronary artery disease (CAD) as this combination allows a comprehensive assessment with regard to presence or absence of coronary atherosclerosis, the extent and severity of coronary plaques, and the haemodynamic relevance of stenosis. In clinical practice, the combination of CT coronary angiography (CCTA) with myocardial perfusion studies obtained by single-photon emission computed tomography (SPECT) and by positron emission tomography (PET) has been well established. Recent literature also reports on the feasibility of combining CCTA with cardiac magnetic resonance imaging. Finally, recent advances in CCTA and SPECT imaging have led to a substantial reduction of radiation exposure, now allowing for comprehensive morphological and functional diagnostic work-up by cardiac hybrid SPECT/CCTA imaging at low radiation dose exposures ranging below 5 mSv.
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Coronary CT Angiography. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-79844-6.

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Karthikeyan, D. Multidetector Coronary CT Angiography. Jaypee Brothers Medical Publishers (P) Ltd., 2008. http://dx.doi.org/10.5005/jp/books/10540.

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Dekker. Atlas of Ct Coronary Angiography. Informa Healthcare, 2006.

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Lee, Christoph I. Diagnostic Performance of CT Coronary Angiography. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190223700.003.0020.

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This chapter, found in the chest pain section of the book, provides a succinct synopsis of a key study examining the diagnostic performance of computed tomography (CT) coronary angiography for patients with chest pain. This summary outlines the study methodology and design, major results, limitations and criticisms, related studies and additional information, and clinical implications. Researchers found that CT angiography accurately detected present and severity of coronary artery disease in certain symptomatic patients, but does not yet replace conventional coronary angiography. In addition to outlining the most salient features of the study, a clinical vignette and imaging example are included in order to provide relevant clinical context.
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Lee, Christoph I. Coronary CT Angiography in Acute Chest Pain. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190223700.003.0022.

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This chapter, found in the chest pain section of the book, provides a succinct synopsis of a key study examining the use of computed tomography (CT) angiography for triaging patients with acute chest pain. This summary outlines the study methodology and design, major results, limitations and criticisms, related studies and additional information, and clinical implications. The study showed that for patients presenting to the emergency department with symptoms suggesting acute coronary syndromes, incorporating early coronary CT angiography into the triage strategy improves diagnostic efficiency, with more direct discharges from the emergency department and shorter lengths of stay for those admitted. In addition to outlining the most salient features of the study, a clinical vignette and imaging example are included in order to provide relevant clinical context.
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Sun, Zhong-Hua. Coronary CT Angiography in the Quantitative Analysis of Coronary Plaques. World Scientific Publishing Co Pte Ltd, 2017.

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Book chapters on the topic "CT Coronary Angiography (CCTA)"

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Green, Michael, Edith M. Marom, Nahum Kiryati, Eli Konen, and Arnaldo Mayer. "A Neural Regression Framework for Low-Dose Coronary CT Angiography (CCTA) Denoising." In Patch-Based Techniques in Medical Imaging, 102–10. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67434-6_12.

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Miclaus, Gratian Dragoslav, and Horia Ples. "Coronary Angiography." In Atlas of CT Angiography, 85–129. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05284-7_4.

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Miclaus, Gratian Dragoslav, and Horia Ples. "Coronary Angiography." In Atlas of CT Angiography, 145–93. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16095-1_5.

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Rumberger, John A. "CT Coronary Angiography." In Cardiac PET and PET/CT Imaging, 191–203. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-38295-1_14.

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Abbasi, Adeel, Francis DeRoos, José Artur Paiva, J. M. Pereira, Brian G. Harbrecht, Donald P. Levine, Patricia D. Brown, et al. "CT Coronary Angiography." In Encyclopedia of Intensive Care Medicine, 641. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-00418-6_1436.

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Schmermund, Axel, Annett Magedanz, Marco J. M. Schmidt, Thomas Schlosser, and Thomas Voigtländer. "Coronary Angiography After Revascularization." In Cardiac CT Imaging, 117–23. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-650-2_10.

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Achenbach, Stephan. "Coronary CT Angiography: Native Vessels." In Cardiac CT Imaging, 99–116. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-650-2_9.

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Eckert, Joachim, Marco Schmidt, Thomas Voigtländer, and Axel Schmermund. "Coronary CT Angiography After Revascularization." In Cardiac CT Imaging, 179–87. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28219-0_10.

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Achenbach, Stephan. "Coronary CT Angiography: Native Vessels." In Cardiac CT Imaging, 157–78. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28219-0_9.

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Bastarrika, Gorka, Carlo Nicola De Cecco, and U. Joseph Schoepf. "CT Angiography of Coronary Stents." In Imaging Coronary Arteries, 115–30. Milano: Springer Milan, 2013. http://dx.doi.org/10.1007/978-88-470-2682-7_13.

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Conference papers on the topic "CT Coronary Angiography (CCTA)"

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Hadjiiski, Lubomir, Chuan Zhou, Heang-Ping Chan, Aamer Chughtai, Prachi Agarwal, Jean Kuriakose, Smita Patel, Jun Wei, and Ella Kazerooni. "Automated registration of coronary arterial trees from multiple phases in coronary CT angiography (cCTA)." In SPIE Medical Imaging, edited by Carol L. Novak and Stephen Aylward. SPIE, 2013. http://dx.doi.org/10.1117/12.2008058.

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Liu, Jordan, Lubomir Hadjiiski, Heang-Ping Chan, Chuan Zhou, Jun Wei, Aamer Chughtai, Jean Kuriakose, Prachi Agarwal, and Ella Kazerooni. "Automatic selection of best quality vessels from multiple-phase coronary CT angiography (cCTA)." In SPIE Medical Imaging, edited by Lubomir M. Hadjiiski and Georgia D. Tourassi. SPIE, 2015. http://dx.doi.org/10.1117/12.2082637.

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Zhou, Chuan, Heang-Ping Chan, Lubomir M. Hadjiiski, Aamer Chughtai, Jun Wei, and Ella A. Kazerooni. "Automated identification of best-quality coronary artery segments from multiple-phase coronary CT angiography (cCTA) for vessel analysis." In SPIE Medical Imaging, edited by Georgia D. Tourassi and Samuel G. Armato. SPIE, 2016. http://dx.doi.org/10.1117/12.2217261.

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Cline, Harvey E., Karthik Krishnan, Sandy Napel, Geoffrey D. Rubin, Wesley D. Turner, and Ricardo S. Avila. "Automated coronary CT angiography plaque-lumen segmentation." In SPIE Medical Imaging, edited by Nico Karssemeijer and Maryellen L. Giger. SPIE, 2009. http://dx.doi.org/10.1117/12.811328.

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Beliveau, P., R. M. Setser, F. Cheriet, R. D. White, and T. O'Donnell. "Computation of coronary perfusion territories from CT angiography." In 2007 34th Annual Computers in Cardiology Conference. IEEE, 2007. http://dx.doi.org/10.1109/cic.2007.4745595.

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Fotin, Sergei V., Anthony P. Reeves, Matthew D. Cham, Claudia I. Henschke, and David F. Yankelevitz. "Segmentation of coronary arteries from CT angiography images." In Medical Imaging, edited by Maryellen L. Giger and Nico Karssemeijer. SPIE, 2007. http://dx.doi.org/10.1117/12.707810.

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Zhang, Lei, Yuzhi He, Hui Zhang, Kang Du, and Guanzhong Gong. "Key-Point Matching Guided Coronary Artery Extraction from CT Coronary Angiography Sequence." In 2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2020. http://dx.doi.org/10.1109/cisp-bmei51763.2020.9263562.

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Lei, Yang, Bang Jun Guo, Yabo Fu, Tonghe Wang, Tian Liu, Walter Curran, Long Jiang Zhang, and Xiaofeng Yang. "Automated coronary artery segmentation in Coronary Computed Tomography Angiography (CCTA) using deep learning neural networks." In Imaging Informatics for Healthcare, Research, and Applications, edited by Thomas M. Deserno and Po-Hao Chen. SPIE, 2020. http://dx.doi.org/10.1117/12.2550368.

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Faber, Tracy L., Cesar A. Santana, Ji Chen, and Ernest V. Garcia. "Fusion of myocardial perfusion data with CT coronary angiography." In 2007 IEEE Nuclear Science Symposium Conference Record. IEEE, 2007. http://dx.doi.org/10.1109/nssmic.2007.4436940.

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Hong, Youngtaek, Frédéric Commandeur, Sebastien Cadet, Markus Goeller, Mhairi Doris, Xi Chen, Jacek Kwiecinski, et al. "Deep learning-based stenosis quantification from coronary CT angiography." In Image Processing, edited by Elsa D. Angelini and Bennett A. Landman. SPIE, 2019. http://dx.doi.org/10.1117/12.2512168.

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