Complex conjugate removal in optical coherence tomography using phase aware generative adversarial network.

Journal: Journal of biomedical optics

PMID: 39963188

Abstract

SIGNIFICANCE: Current methods for complex conjugate removal (CCR) in frequency-domain optical coherence tomography (FD-OCT) often require additional hardware components, which increase system complexity and cost. A software-based solution would provide a more efficient and cost-effective alternative.

Authors

Valentina Bellemo

Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
Richard Haindl

Medical University of Vienna, Center for Medical Physics and Biomedical Engineering, Vienna, Austria.
Manojit Pramanik

School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore, 637459 Singapore.
Linbo Liu

School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
Leopold Schmetterer

Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
Xinyu Liu

Institute of Medical Technology, Peking University Health Science Center, Beijing, China.

Keywords

Algorithms Animals Artifacts Deep Learning Eye Generative Adversarial Networks Humans Image Processing, Computer-Assisted Mice Phantoms, Imaging Skin Tomography, Optical Coherence

External Resources

View on PubMed Access via DOI PubMed (39963188)

Complex conjugate removal in optical coherence tomography using phase aware generative adversarial network.

Abstract

Authors

Keywords

External Resources

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