Open AccessUltrasound-based carotid stenosis measurement and risk stratification in diabetic cohort: a deep learning paradigm
Author(s) -
Luca Saba,
Mainak Biswas,
Harman S. Suri,
Klaudija Višković,
John R. Laird,
Elisa Cuadrado-Godia,
Andrew Nicolaides,
Narendra N. Khanna,
Vijay Viswanathan,
Jasjit S. Suri
Publication year - 2019
Publication title -
cardiovascular diagnosis and therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 22
eISSN - 2223-3660
pISSN - 2223-3652
DOI - 10.21037/cdt.2019.09.01
Subject(s) - medicine , stenosis , receiver operating characteristic , risk stratification , carotid arteries , stroke (engine) , ultrasound , lumen (anatomy) , radiology , cohort , gold standard (test) , common carotid artery , cardiology , artificial intelligence , computer science , mechanical engineering , engineering
Stroke is in the top three leading causes of death worldwide. Non-invasive monitoring of stroke can be accomplished via stenosis measurements. The current conventional image-based methods for these measurements are not accurate and reliable. They do not incorporate shape and intelligent learning component in their design.