scholarly journals Coronary Artery Tracking in 3D Cardiac CT Images Using Local Morphological Reconstruction Operators

2008 ◽  
Author(s):  
Carlos Castro ◽  
Miguel �ngel Luengo-Oroz ◽  
Andr� Santos ◽  
Mar�a J. Ledesma-Carbayo
Keyword(s):  
Coronary Artery ◽  
Automatic Segmentation ◽  
Multislice Ct ◽  
Ct Images ◽  
General Strategy ◽  
Centerline Extraction ◽  
Artery Disease ◽  
Vessel Extraction ◽  
Future Work ◽  
Coronary Artery Tree

Automatic segmentation and tracking of the coronary artery tree from Cardiac Multislice-CT images is an important goal to improve the diagnosis and treatment of coronary artery disease. This paper presents a semi-automatic algorithm (one input point per vessel) based on morphological grayscale local reconstructions in 3D images devoted to the extraction of the coronary artery tree. The algorithm has been evaluated in the framework of the Coronary Artery Tracking Challenge 2008 [1], obtaining consistent results in overlapping measurements (a mean of 70% of the vessel well tracked). Poor results in accuracy measurements suggest that future work should refine the centerline extraction. The algorithm can be efficiently implemented and its general strategy can be easily extrapolated to a completely automated centerline extraction or to a user interactive vessel extraction.

scholarly journals Review. Automatic Segmentation Techniques of the Coronary Artery Using CT Images in Acute Coronary Syndromes

2017 ◽  
Vol 3 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Sándor Miklós Szilágyi ◽  
Monica Marton Popovici ◽  
László Szilágyi
Keyword(s):  
Coronary Artery ◽  
Acute Coronary Syndromes ◽  
Vascular System ◽  
Imaging Techniques ◽  
Automatic Segmentation ◽  
Patients At Risk ◽  
Coronary Syndromes ◽  
Artery Disease ◽  
Coronary Artery Tree

AbstractCoronary artery disease represents one of the leading reasons of death worldwide, and acute coronary syndromes are their most devastating consequences. It is extremely important to identify the patients at risk for developing an acute myocardial infarction, and this goal can be achieved using noninvasive imaging techniques. Coronary computed tomography angiography (CCTA) is currently one of the most reliable methods used for assessing the coronary arteries; however, its use in emergency settings is sometimes limited due to time constraints. This paper presents the main characteristics of plaque vulnerability, the role of CCTA in the assessment of vulnerable plaques, and automatic segmentation techniques of the coronary artery tree based on CT angiography images. A detailed inventory of existing methods is given, representing the state-of-the-art of computational methods applied in vascular system segmentation, focusing on the current applications in acute coronary syndromes.

Unprotected left main intervention for surgery-ineligible patients with coronary artery disease—Usefulness of micro-CT images for stent

2016 ◽  
Vol 221 ◽  
pp. 385-389
Author(s):  
Daisuke Sueta ◽  
Yuichiro Arima ◽  
Seiji Hokimoto ◽  
Toshifumi Mukunoki ◽  
Noriaki Tabata ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Ct Images ◽  
Micro Ct ◽  
Left Main ◽  
Artery Disease ◽  
Main Intervention

Fully-automatic segmentation of coronary artery using growing algorithm

2020 ◽  
Vol 28 (6) ◽  
pp. 1171-1186
Author(s):  
Jiali Cui ◽  
Hua Guo ◽  
Huafeng Wang ◽  
Fuqiang Chen ◽  
Lixia Shu ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Coronary Arteries ◽  
Automatic Segmentation ◽  
Disease Diagnosis ◽  
Cardiac Computed Tomography Angiography ◽  
Fully Automatic ◽  
Artery Disease ◽  
Growing Strategy ◽  
Coronary Artery Disease Diagnosis

Currently, cardiac computed tomography angiography (CTA) is widely applied to coronary artery disease diagnosis. Automatic segmentation of coronary artery has played an important role in coronary artery disease diagnosis. In this study, we propose and test a fully automatic coronary artery segmentation method that does not require any human-computer interaction. The proposed method uses a growing strategy and contains three main parts namely, (1) the initial seed detection that automatically detects the root points of the left and right coronary arteries where the ascending aorta meets the coronary arteries, (2) the growing strategy that searches for the neighborhood blocks to decide the existence of coronary arteries with an improved convolutional neural network, and (3) the iterative termination condition that decides whether the growing iteration finishes. The proposed framework is validated using a dataset containing 32 cardiac CTA volumes from different patients for training and testing. Experimental results show that the proposed method obtained a Dice loss ranged from 0.70 to 0.83, which indicates that the new method outperforms the traditional methods such as level set.

scholarly journals Lower extremity arterial calcifications assessed by multislice CT as a correlate to coronary artery disease

2020 ◽  
Vol 51 (1) ◽  
Author(s):  
Gamal Samir Gamal Aly ◽  
Hussien Heshmat Kassem ◽  
Assem Hashad ◽  
Mohammad Ali Salem ◽  
Dina Labib ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Lower Extremity ◽  
Multislice Ct ◽  
Artery Disease
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