TY - GEN
T1 - Deep Learning for Time-Domain Diffuse Optical Tomography Reconstructions by Unrolling a Sensitivity Equation-based Algorithm
AU - Wang, Fay
AU - Hielscher, Andreas H.
AU - Kim, Stephen H.
N1 - Publisher Copyright:
© 2023 The Author (s)
PY - 2023
Y1 - 2023
N2 - We have developed a neural network based on algorithm unrolling techniques to overcome challenges in the DOT inverse problem. Results from numerical and phantom experiments show the network’s capability for high-speed and accurate DOT reconstructions.
AB - We have developed a neural network based on algorithm unrolling techniques to overcome challenges in the DOT inverse problem. Results from numerical and phantom experiments show the network’s capability for high-speed and accurate DOT reconstructions.
UR - http://www.scopus.com/inward/record.url?scp=85191180666&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85191180666&partnerID=8YFLogxK
U2 - 10.1364/NTM.2023.JTu4B.7
DO - 10.1364/NTM.2023.JTu4B.7
M3 - Conference contribution
AN - SCOPUS:85191180666
T3 - Novel Techniques in Microscopy, NTM 2023
BT - Novel Techniques in Microscopy, NTM 2023
PB - Optical Society of America
T2 - Novel Techniques in Microscopy, NTM 2023 - Part of Optica Biophotonics Congress: Optics in the Life Sciences 2023
Y2 - 24 April 2023 through 27 April 2023
ER -