Coronary artery curvature extraction using physic-based model in intravascular ultrasound image sequence

2016 ◽  
Author(s):  
Ali Kermani ◽  
Ahmad Ayatollahi ◽  
Arash Taki
Keyword(s):  
Coronary Artery ◽  
Intravascular Ultrasound ◽  
Ultrasound Image ◽  
Image Sequence

scholarly journals Calcification detection using convolutional neural network architectures in Intravascular ultrasound images

2020 ◽  
Vol 17 (3) ◽  
pp. 1313
Author(s):  
Hannah Sofian ◽  
Joel Than Chia Ming ◽  
Suraya Muhammad ◽  
Norliza Mohd Noor
Keyword(s):  
Neural Network ◽  
Cardiovascular Disease ◽  
Coronary Artery ◽  
Convolutional Neural Network ◽  
Intravascular Ultrasound ◽  
Predictive Value ◽  
Area Under Curve ◽  
Ultrasound Image ◽  
Network Architectures ◽  
Neural Network Architectures

<p>Cardiovascular disease is the highest leading to death for Non-Communicable disease. Coronary artery calcification disease is part of cardiovascular disease. The built-in of the plaques and the calcification in the coronary artery inner wall make the blood vessel cross-section area narrow. The standard practice by the radiologists and medical clinical are by visual inspection to detect the calcification in the intravascular ultrasound image. Deep learning is the current image processing methods that have high potential to detect calcification analysis using convolutional neural network architecture and classifiers. To detect the absence of calcification and presence calcification on the intravascular ultrasound image, using k-fold =10, we compared the three types of convolutional neural network architectures and the seven types of classifiers with the provided ground truth from MICCAI 2011. We used two types of images named as Cartesian Coordinates image and polar reconstructed coordinate image. The classifiers such as Support Vector Machine, Discriminant analysis, Ensembles and Error-Correcting Output Codes obtained the perfect result with value one for Area Under Curve and all the performance measure result, accuracy, sensitivity, specificity, positive predictive value and negative predictive value. Area Under Curve for Naïve Bayes classifier is 0.9967 and for Decision Tree classifier is 0.9994, obtained using the polar reconstructed coordinate image for InceptionresNet-V2 architecture.</p>

Fuzzy inference-based plaque boundary extraction using image separability for intravascular ultrasound image of coronary artery

2009 ◽  
Vol 45 (9) ◽  
pp. 451 ◽  
Author(s):  
E. Uchino ◽  
N. Suetake ◽  
T. Koga ◽  
R. Kubota ◽  
S. Ichiyama ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Intravascular Ultrasound ◽  
Fuzzy Inference ◽  
Ultrasound Image ◽  
Boundary Extraction

A Parallel Method for Segmenting Intravascular Ultrasound Image Sequence

2011 ◽  
Vol 130-134 ◽  
pp. 2051-2055 ◽  
Author(s):  
Zheng Sun ◽  
Cun Liu
Keyword(s):  
Intravascular Ultrasound ◽  
Vessel Wall ◽  
Ultrasound Image ◽  
Vascular Diseases ◽  
Image Sequence ◽  
Coronary Artery Diseases ◽  
Parallel Method ◽  
Cross Sectional ◽  
Ivus Image ◽  
Vessel Reconstruction

Intravascular Ultrasound (IVUS) is one of interventional imaging modalities widely used in clinical diagnosis of vascular diseases, especially coronary artery diseases. Segmentation of IVUS images to extract vessel wall boundaries is of importance for quantitative analysis and 3D vessel reconstruction. A 3D parallel method for segmenting IVUS image sequence is proposed in this paper. Firstly, original images are preprocessed to reduce possible noises and eliminate ring-down artifacts. Then, several longitudinal cuts are obtained and intima-lumen and media-adventitia boundaries are detected. Once these boundaries are mapped onto each cross-sectional slice, initial plan of vessel wall boundaries in each frame is obtained. Finally, these initial contours evolve continuously until stop at target contours. Consequently, segmentation of each IVUS tomographic frame is implemented simultaneously and the efficiency is greatly raised compared with 2D sequential approaches.

Sign in / Sign up

Export Citation Format

Share Document