Deep Learning for Motion Artifact-Suppressed OCTA Image Generation from Both Repeated and Adjacent OCT Scans

Deep Learning for Motion Artifact-Suppressed OCTA Image Generation from Both Repeated and Adjacent OCT Scans

Optical coherence tomography angiography (OCTA) is a popular technique for imaging microvascular networks, but OCTA image quality is commonly affected by motion artifacts. Deep learning (DL) has been used to generate OCTA images from structural OCT images, yet limitations persist, such as low label...

Full description

Bibliographic Details
Main Authors: Zhefan Lin, Qinqin Zhang, Gongpu Lan, Jingjiang Xu, Jia Qin, Lin An, Yanping Huang
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Mathematics
Subjects:
optical coherence tomography angiography
deep learning
image fusion
image generation
neighborhood information
training scheme
Online Access:https://www.mdpi.com/2227-7390/12/3/446

Similar Items

Similar Items