scholarly journals Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Yun Tian ◽  
Yutong Pan ◽  
Fuqing Duan ◽  
Shifeng Zhao ◽  
Qingjun Wang ◽  
...  
Keyword(s):  
Coronary Arteries ◽  
Cardiac Computed Tomography ◽  
Similarity Index ◽  
Region Growing ◽  
Volume Data ◽  
Cardiac Computed Tomography Angiography ◽  
Decision Method ◽  
Data Volume ◽  
Seed Points ◽  
Dice Similarity Index

The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA) volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.

scholarly journals Appropriate utilization of cardiac computed tomography for the assessment of stable coronary artery disease

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Michael Hammer ◽  
Muhtashim Mian ◽  
Levi Elhadad ◽  
Mary Li ◽  
Idan Roifman
Keyword(s):  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiac Imaging ◽  
Cardiac Computed Tomography ◽  
The United States ◽  
Appropriate Use ◽  
Potential Cost ◽  
Cardiac Computed Tomography Angiography ◽  
Artery Disease

Abstract Background Appropriate use criteria (AUC) have been developed in response to growth in cardiac imaging utilization and concern regarding associated costs. Cardiac computed tomography angiography (CCTA) has emerged as an important modality in the evaluation of coronary artery disease, however its appropriate utilization in actual practice is uncertain. Our objective was to determine the appropriate utilization of CCTA in a large quaternary care institution and to compare appropriate utilization pre and post publication of the 2013 AUC guidelines. We hypothesized that the proportion of appropriate CCTA utilization will be similar to those of other comparable cardiac imaging modalities and that there would be a significant increase in appropriate use post AUC publication. Methods We employed a retrospective cohort study design of 2577 consecutive patients undergoing CCTA between January 1, 2012 and December 30, 2016. An appropriateness category was assigned for each CCTA. Appropriateness classifications were compared pre- and post- AUC publication via the chi-square test. Results Overall, 83.5% of CCTAs were deemed to be appropriate based on the AUC. Before the AUC publication, 75.0% of CCTAs were classified as appropriate whereas after the AUC publication, 88.0% were classified as appropriate (p < 0.001). The increase in appropriate utilization, when extrapolated to the Medicare population of the United States, was associated with potential cost savings of approximately $57 million per year. Conclusions We report a high rate of appropriate use of CCTA and a significant increase in the proportion of CCTAs classified as appropriate after the AUC publication.

scholarly journals Coronary Centerline Extraction from CCTA Using 3D-UNet

2021 ◽  
Vol 13 (4) ◽  
pp. 101
Author(s):  
Alexandru Dorobanțiu ◽  
Valentin Ogrean ◽  
Remus Brad
Keyword(s):  
Computed Tomography ◽  
Cardiac Computed Tomography ◽  
Three Dimensional ◽  
Class Imbalance ◽  
Training Data ◽  
Cardiac Computed Tomography Angiography ◽  
Centerline Extraction ◽  
Network Training ◽  
Dimensional Reconstruction ◽  
Coronary Centerline

The mesh-type coronary model, obtained from three-dimensional reconstruction using the sequence of images produced by computed tomography (CT), can be used to obtain useful diagnostic information, such as extracting the projection of the lumen (planar development along an artery). In this paper, we have focused on automated coronary centerline extraction from cardiac computed tomography angiography (CCTA) proposing a 3D version of U-Net architecture, trained with a novel loss function and with augmented patches. We have obtained promising results for accuracy (between 90–95%) and overlap (between 90–94%) with various network training configurations on the data from the Rotterdam Coronary Artery Centerline Extraction benchmark. We have also demonstrated the ability of the proposed network to learn despite the huge class imbalance and sparse annotation present in the training data.

scholarly journals Aspartame Intake Relates to Coronary Plaque Burden and Inflammatory Indices in Human Immunodeficiency Virus

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
Leangelo N. Hall ◽  
Laura R. Sanchez ◽  
Jane Hubbard ◽  
Hang Lee ◽  
Sara E. Looby ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Cardiac Computed Tomography ◽  
Coronary Plaque ◽  
Plaque Burden ◽  
Artificial Sweetener ◽  
Food Record ◽  
Cvd Risk ◽  
Cardiac Computed Tomography Angiography ◽  
Markers Of Inflammation ◽  
Immunodeficiency Virus

Abstract Background Dietary sweeteners may contribute to metabolic dysregulation and cardiovascular disease (CVD), but this has not been assessed in human immunodeficiency virus (HIV). Methods One hundred twenty-four HIV-infected and 56 non-HIV-infected participants, without history of known coronary artery disease were included. Dietary intake was assessed using a 4-day food record. Coronary plaque was determined using cardiac computed tomography angiography. Results Human immunodeficiency virus-infected participants had significantly greater intake of dietary sweeteners, including total sugar (P = .03) and added sugar (P = .009); intake of aspartame (artificial sweetener) was greater among aspartame consumers with HIV versus non-HIV consumers (P = .03). Among HIV-infected participants, aspartame intake was significantly associated with coronary plaque (P = .002) and noncalcified plaque (P = .007) segments, as well as markers of inflammation/immune activation (monocyte chemoattractant protein 1 and lipoprotein-associated phospholipase A2), which may contribute to increased atherogenesis. In multivariable regression modeling, aspartame remained an independent predictor of plaque in HIV. In contrast, among non-HIV-infected participants, no sweetener type was shown to relate to plaque characteristics. Conclusions We demonstrate increased intake of dietary sweeteners and a potential novel association between aspartame intake, plaque burden, and inflammation in HIV. Our data suggest that aspartame may contribute to CVD risk in HIV. Further studies should address potential mechanisms by which aspartame may contribute to increased plaque burden and cardiovascular benefits of dietary strategies targeting aspartame intake in HIV.

Open Source Software Implementation of Anatomical Segmentation

2018 ◽  
Author(s):  
Maggie Hess
Keyword(s):  
Large Scale ◽  
Focused Ultrasound ◽  
Region Growing ◽  
Ground Truth ◽  
Clot Lysis ◽  
Focused Ultrasound Surgery ◽  
Manual Methods ◽  
Areas Of Interest ◽  
Seed Points ◽  
Viable Method

Purpose: Intraventricular hemorrhage (IVH) affects nearly 15% of preterm infants. It can lead to ventricular dilation and cognitive impairment. To ablate IVH clots, MR-guided focused ultrasound surgery (MRgFUS) is investigated. This procedure requires accurate, fast and consistent quantification of ventricle and clot volumes. Methods: We developed a semi-autonomous segmentation (SAS) algorithm for measuring changes in the ventricle and clot volumes. Images are normalized, and then ventricle and clot masks are registered to the images. Voxels of the registered masks and voxels obtained by thresholding the normalized images are used as seed points for competitive region growing, which provides the final segmentation. The user selects the areas of interest for correspondence after thresholding and these selections are the final seeds for region growing. SAS was evaluated on an IVH porcine model.  Results: SAS was compared to ground truth manual segmentation (MS) for accuracy, efficiency, and consistency. Accuracy was determined by comparing clot and ventricle volumes produced by SAS and MS. In Two-One-Sided Test, SAS and MS were found to be significantly equivalent (p < 0.01). SAS on average was found to be 15 times faster than MS (p < 0.01). Consistency was determined by repeated segmentation of the same image by both SAS and manual methods, SAS being significantly more consistent than MS (p < 0.05).  Conclusion: SAS is a viable method to quantify the IVH clot and the lateral brain ventricles and it is serving in a large- scale porcine study of MRgFUS treatment of IVH clot lysis.

scholarly journals Cardiovascular Imaging Techniques for Detection of Vulnerable Plaques

2021 ◽  
Vol 6 (1) ◽  
pp. 21-26
Author(s):  
Emese Márton ◽  
Daniel Cernica ◽  
Cosmin Țolescu ◽  
Andrada Lupșan ◽  
Monica Chițu ◽  
...  
Keyword(s):  
Morphological Changes ◽  
Imaging Techniques ◽  
Cardiac Computed Tomography ◽  
Cardiovascular Imaging ◽  
Scientific Data ◽  
Ultra Sound ◽  
Plaque Vulnerability ◽  
Cardiac Computed Tomography Angiography ◽  
Coronary Syndrome ◽  
Atheromatous Plaques

Abstract Various cardiovascular imaging techniques were developed for the detection of vulnerable atherosclerotic plaques, hoping to be able to predict a cardiovascular event. Plaque vulnerability results from compound pathophysiological mechanisms that lead to structural and morphological changes in lesions. The aim of this review is to present the most recent techniques for the assessment of vulnerable coronary plaques such as cardiac computed tomography angiography (CCTA), optical coherence tomography, or virtual histology intravascular ultra-sound, based on literature data from the last 3 years. CCTA permits direct visualization of the intravascular lumen, together with characterization of the arterial wall. Recent studies maintain that low-attenuation plaques, spotty calcifications, positive vessel remodeling, and the napkin-ring sign are considered main markers of plaque vulnerability and instability. Emerging analytical techniques, such as machine learning or radiomics, will probably demonstrate useful as an auxiliary diagnostic tool for vulnerable plaque detection. The data from the two imaging techniques together provide useful information, especially in patients undergoing a PCI procedure for an acute coronary syndrome. Invasive and noninvasive imaging techniques are able to deliver a large amount of scientific data to assess vulnerable coronary atheromatous plaques. Recent studies demonstrated that information defined by the two techniques is complementary, and using both methods is essential for adequate diagnosis, therapeutic strategy, and prognostic assessment.

scholarly journals Analysis of Tools for The Description and Analytical Processing of Enviromental Data

2020 ◽  
Vol 20 (2) ◽  
pp. 129-132
Author(s):  
Vugar Abdullayev ◽  
N.A. Ragimova N.A ◽  
V.H Abdullayev ◽  
T.K Askerov
Keyword(s):  
Data Processing ◽  
Environmental Monitoring ◽  
Analytical Data ◽  
Environmental Data ◽  
Volume Data ◽  
Star Schema ◽  
Data Processing Tool ◽  
Data Volume ◽  
Speed Up ◽  
Analytical Processing

The objects of the research are tools that support the description and analytical processing of environmental data requests. These tools are used for environmental monitoring. Analytical processing of environmental data is necessary for this monitoring by the persons concerned. Here, a star schema is used to describe the data. Analytical data processing tools are required for analysis and research of environmental data. The results of analytical processing of environmental data are used to speed up decision-making. This article also describes the structure of the analytical data processing tool. Therefore, one of the problem points is how to describe the data. For this purpose, an environmental data relay scheme is defined, and the data description is implemented in multidimensional cubes. Due to the growth of data volume, data processing is carried out using multi-dimensional visualization methods. In addition, a visual user interface has been created for analytically processing queries based on scale data. The result of this research is to find a method for describing environmental data. At the end of the research, a hypercube was obtained, with the help of which it was possible to structure environmental data and carry out analytical processing of them. To this end, environmental data have been described using a multi-dimensional visualization method. And OLAP technologies were used to carry out analytical processing of this data. OLAP technologies allow aggregate data to be used and presented as a hypercube. The results of the research can be used as a basis for an environmental information system that is used for environmental monitoring.

Sign in / Sign up

Export Citation Format

Share Document