Detecting Carotid Intima-Media From Small-Sample Ultrasound Images

Mi, Shiyu; Wei, Zhanghong; Xu, Jinfeng; Yü, Zhihui; Yang, Wenming; Liao, Qingmin

doi:10.1109/embc44109.2020.9176282

Cited by 2 publications

(1 citation statement)

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“…Convolutional neural network (CNN) is widely used in image segmentation by extracting features through convolution operation and performing subsequent classification and recognition. Mi et al [10] proposed a new IMC detection method based on CNN, firstly the region of interest (ROI) is automatically extracted by morphological processing, then the patchwise training data are constructed, and finally a simple CNN is trained to detect the IMC. Jayanthi et al [11] used the deep CNN network to automatically delimit ROI for the original input image, and used the snake model to segment the boundary of the IMC.…”

Section: Segmentation Of the Imc In Longitudinal Ultrasoundmentioning

confidence: 99%

Advances in Intelligent Segmentation and 3D/4D Reconstruction of Carotid Ultrasound Imaging

Cui¹,

Li²,

Lin³

2023

Advanced Ultrasound in Diagnosis and Therapy

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Cardiovascular disease (CVD) is one of the ten leading causes of death worldwide. Atherosclerotic disease, which can lead to myocardial infarction and stroke, is the main cause of CVD. The two main ultrasound image phenotypes used to monitor atherosclerotic load are carotid intima-media thickness (IMT) and plaque area (PA). Early segmentation and measurement methods were based on manual or threshold segmentation, snake models, etc. Usually, these methods are semi-automatic and have poor repeatability and accuracy. Segmentation of the carotid intima-media complex (IMC) and plaque in ultrasound based on artificial intelligence can achieve good accuracy. Compared with two-dimensional ultrasound, three-dimensional/fourdimensional ultrasound can provide spatial dynamic vascular information, which is helpful for doctors to evaluate. This study reviews the progress of artificial intelligence (AI) segmentation methods based on machine learning (ML) and deep learning (DL) used in the segmentation of the IMC and plaque as well as the 3D / 4D reconstruction of carotid ultrasound.

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Section: Segmentation Of the Imc In Longitudinal Ultrasoundmentioning

confidence: 99%