TY - GEN
T1 - Unsupervised Learning-Based Registration Method for Photoacoustic Microscopy Image Sequences
AU - Tang, Furong
AU - Hong, Xiaobin
AU - Wang, Lidai
AU - Chen, Jiangbo
PY - 2025/6
Y1 - 2025/6
N2 - An unsupervised deep learning network for real-time correction and registration of fast-scanning photoacoustic microscopy images has been developed, improving speed by 50 times and outperforming traditional methods in extracting dynamic vascular information. © 2025 The Author(s)
AB - An unsupervised deep learning network for real-time correction and registration of fast-scanning photoacoustic microscopy images has been developed, improving speed by 50 times and outperforming traditional methods in extracting dynamic vascular information. © 2025 The Author(s)
UR - http://www.scopus.com/inward/record.url?scp=105031881341&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-105031881341&origin=recordpage
U2 - 10.1364/ECBO.2025.Tu2A.38
DO - 10.1364/ECBO.2025.Tu2A.38
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781557528001
T3 - European Conference on Biomedical Optics, ECBO
BT - European Conference on Biomedical Optics 2025
PB - Optical Society of America
T2 - 2025 European Conference on Biomedical Optics (ECBO 2025)
Y2 - 22 June 2025 through 26 June 2025
ER -