scholarly journals A Comparative Study of Three Speckle Reducing Methods for Intima-Media Thickness Ultrasound Images

2015 ◽  
Vol 17 (2) ◽  
Author(s):  
Mehravar Rafati ◽  
Masoud Arabfard ◽  
Mehrdad Rafati Rahimzadeh ◽  
Hasan Voshtani ◽  
Hassan Moladoust
Keyword(s):  
Comparative Study ◽  
Intima Media Thickness ◽  
Ultrasound Images ◽  
Media Thickness

Segmentation and Measurements of Carotid Intima-Media Thickness in Ultrasound Images Using the Improved Convolutional Neural Network and Support Vector Machine

2021 ◽  
Vol 11 (1) ◽  
pp. 15-24
Author(s):  
Dequan Guo ◽  
Gexiang Zhang ◽  
Hui Peng ◽  
Jianying Yuan ◽  
Prithwineel Paul ◽  
...  
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Convolutional Neural Network ◽  
Intima Media Thickness ◽  
Ground Truth ◽  
Classification Model ◽  
Support Vector ◽  
Ultrasound Images ◽  
Boundary Points ◽  
Media Thickness

In recent years, diseases of cardiovascular and cerebrovascular have attracted much attention due to main causes in death in human beings. To reduce mortality, there are lots of efforts which are focused on early diagnosis and prevention. It is an important reference index for cardiovascular diseases through the endovascular membrane in carotid artery by medical ultrasound images. The paper proposes a method which finds the region of interest (ROI) by convolutional neural network, segments and measures intima-media membrane mainly using support vector machine (SVM). Essentially, the task of detecting the membrane is one target detection problem. This paper adopts the strategy, named Yon Only Look Once (YOLO), a new detection algorithm, and follows the convolution neural network algorithm based on end-to-end training. Firstly, sufficient samples are extracted according to certain characteristics in the special region. It can be trained by the SVM classification model. Then the ROI is processed and all the pixels are classified into boundary points and non-boundary points through the classification model. Thirdly, the boundary points are selected to obtain the accurate boundary and calculate the intima-media thickness (IMT). In experiments, two hundred ultrasound images are tested, and the results verify that our algorithm is consistent with the results by ground truth (GT). The detection speed of the algorithm in this paper is in real time, and it has high generalization characteristics. The algorithm computes the intima-media thickness in ultrasound images accurately and quickly with 95% consistence to ground truth.

scholarly journals An Improved Approach for Accurate and Efficient Measurement of Common Carotid Artery Intima-Media Thickness in Ultrasound Images

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Qiang Li ◽  
Wei Zhang ◽  
Xin Guan ◽  
Yu Bai ◽  
Jing Jia
Keyword(s):  
Carotid Artery ◽  
Common Carotid Artery ◽  
Intima Media Thickness ◽  
Ground Truth ◽  
Low Complexity ◽  
Computational Time ◽  
Ultrasound Images ◽  
Important Indicator ◽  
Media Thickness ◽  
Efficient Measurement

The intima-media thickness (IMT) of common carotid artery (CCA) can serve as an important indicator for the assessment of cardiovascular diseases (CVDs). In this paper an improved approach for automatic IMT measurement with low complexity and high accuracy is presented. 100 ultrasound images from 100 patients were tested with the proposed approach. The ground truth (GT) of the IMT was manually measured for six times and averaged, while the automatic segmented (AS) IMT was computed by the algorithm proposed in this paper. The mean difference ± standard deviation between AS and GT IMT is 0.0231 ± 0.0348 mm, and the correlation coefficient between them is 0.9629. The computational time is 0.3223 s per image with MATLAB under Windows XP on an Intel Core 2 Duo CPU E7500 @2.93 GHz. The proposed algorithm has the potential to achieve real-time measurement under Visual Studio.

Associations of edge-detected and manual-traced common carotid artery intima-media thickness with incident peripheral artery disease: The Multi-Ethnic Study of Atherosclerosis

2019 ◽  
Vol 24 (4) ◽  
pp. 306-312
Author(s):  
Joseph F Polak ◽  
David Herrington ◽  
Daniel H O’Leary
Keyword(s):  
Carotid Artery ◽  
Peripheral Artery Disease ◽  
Common Carotid Artery ◽  
Intima Media Thickness ◽  
Cox Proportional Hazards ◽  
Ultrasound Images ◽  
Peripheral Artery ◽  
Ethnic Study ◽  
Media Thickness ◽  
Artery Disease

Common carotid artery (CCA) intima-media thickness (IMT) is associated with coronary heart disease and can be measured on ultrasound images either by hand or with an automated edge detector. The association of CCA IMT with incident peripheral artery disease (PAD) is poorly studied. We studied 5467 participants of the Multi-Ethnic Study of Atherosclerosis composed of non-Hispanic white, Chinese, Hispanic, and African American participants with a mean age of 61.9 years (47.8% men). Framingham Risk Factors, manual-traced IMT (mt-IMT), and edge-detected IMT (ed-IMT) were entered into multivariable Cox proportional hazards models with incident PAD as the outcome. There were 87 events during a median follow-up of 12.2 years. In fully adjusted models and expressing the hazard ratios (HR) as an increment in SD values, both mt-IMT and ed-IMT were significantly associated with incident PAD: HR 1.36 (95% CI: 1.15, 1.61) and 1.29 (95% CI: 1.04, 1.60), respectively. We conclude that ed- and mt-CCA IMT measurements are associated with incident PAD. ClinicalTrials.gov Identifier: NCT00063440

scholarly journals Filtering and Detection of Intima-media Thickness (IMT) for the risk of Carotid Artery Atherosclerosis

2019 ◽  
Vol 9 (2) ◽  
pp. 4900-4903
Keyword(s):  
Carotid Artery ◽  
Intima Media Thickness ◽  
Ultrasound Images ◽  
Carotid Artery Atherosclerosis ◽  
Local Characteristics ◽  
Media Thickness ◽  
Human Effort ◽  
Edge Detection Method ◽  
Mean Variance

Ultrasound images of carotid artery in brightness mode (B-mode) are used to detect the probabilities of atherosclerosis and cardiovascular diseases. They are used to measure the intima-media thickness (IMT). Ultrasound images suffer from peculiar phenomena which creates speckle (a type of noise) on the image. The speckles present in the medical images detoriates the quality of the image. This paper presents a work which is used to remove the speckles by utilizing the local characteristics of the image in the filter named as local statistics mean variance (lsmv) filter. It is a preprocessing step of medical image processing. Conventional IMT was done by locating the far walls of the carotid artery. This can be changed by applying segmentation algorithm which could automatically detect the far walls and could measure the IMT. This paper approaches towards automatic edge detection method using Prewitt operator. The objective behind automatically calculating IMT of carotid artery is to reduce the human effort and at the same time would benefit the patient by diagnosing the patient condition. The work that is proposed is analyzed by calculating various parameters in case of despeckling (filtering) as well as segmentation method. The performance parameters show that the proposed method performs better and at the same time reduces the manual effort.

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