Identification of coronary calcifications in optical coherence tomography imaging using deep learning
Abstract Coronary calcifications are an obstacle for successful percutaneous treatment of coronary artery disease patients. The optimal method for delineating calcifications extent is coronary optical coherence tomography (OCT). To identify calcification on OCT and subsequently tailor the appropriat...
Enregistré dans:
Auteurs principaux: | Yarden Avital, Akiva Madar, Shlomi Arnon, Edward Koifman |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/2347b670f0914ebb8467a552cfaa9f95 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Synthetic polarization-sensitive optical coherence tomography by deep learning
par: Yi Sun, et autres
Publié: (2021) -
Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence
par: Peter M. Maloca, et autres
Publié: (2021) -
Segmentation of Preretinal Space in Optical Coherence Tomography Images Using Deep Neural Networks
par: Agnieszka Stankiewicz, et autres
Publié: (2021) -
High-resolution polarization-sensitive optical coherence tomography and optical coherence tomography angiography for zebrafish skin imaging
par: Di Yang, et autres
Publié: (2021) -
Comparison of enhanced depth imaging and high-penetration optical coherence tomography for imaging deep optic nerve head and parapapillary structures
par: Miki A, et autres
Publié: (2013)