AIMC Topic: Adventitia

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A Deep Learning-based Method to Extract Lumen and Media-Adventitia in Intravascular Ultrasound Images.

Ultrasonic imaging
Intravascular ultrasound (IVUS) imaging allows direct visualization of the coronary vessel wall and is suitable for assessing atherosclerosis and the degree of stenosis. Accurate segmentation and lumen and median-adventitia (MA) measurements from IVU...

Deep learning-based carotid media-adventitia and lumen-intima boundary segmentation from three-dimensional ultrasound images.

Medical physics
PURPOSE: Quantification of carotid plaques has been shown to be important for assessing as well as monitoring the progression and regression of carotid atherosclerosis. Various metrics have been proposed and methods of measurements ranging from manua...

An artificial neural network method for lumen and media-adventitia border detection in IVUS.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Intravascular ultrasound (IVUS) has been well recognized as one powerful imaging technique to evaluate the stenosis inside the coronary arteries. The detection of lumen border and media-adventitia (MA) border in IVUS images is the key procedure to de...

Extracting Membrane Borders in IVUS Images Using a Multi-Scale Feature Aggregated U-Net.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic extraction of the lumen-intima border (LIB) and the media-adventitia border (MAB) in intravascular ultrasound (IVUS) images is of high clinical interest. Despite the superior performance achieved by deep neural networks (DNNs) on various me...