TY - JOUR
T1 - Anomaly detection inside diffuse media using deep learning algorithm
AU - Wiesel, Ben
AU - Arnon, Shlomi
N1 - Funding Information: This project received partial funding from the European Union’s Horizon 2020 research and innovation program (Future and Emerging Technologies) under Grant Agreement No. 828978; the Israeli Ministry of Science and Technology and the Ben Gurion University of the Negev internal student fellowship. Publisher Copyright: ©2021TheAuthor(s)
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Novel deep-learning algorithm is utilized to detect simulated tumors embedded inside 3D turbid media using a small set of sources and detectors. Thus, proving the utility of deep-learning methods for solving diffuse imaging 3D inverse problems.
AB - Novel deep-learning algorithm is utilized to detect simulated tumors embedded inside 3D turbid media using a small set of sources and detectors. Thus, proving the utility of deep-learning methods for solving diffuse imaging 3D inverse problems.
UR - http://www.scopus.com/inward/record.url?scp=85119455931&partnerID=8YFLogxK
M3 - Conference article
SN - 2162-2701
JO - Optics InfoBase Conference Papers
JF - Optics InfoBase Conference Papers
M1 - ETu2A.8
T2 - 2021 European Conferences on Biomedical Optics, ECBO 2021
Y2 - 20 June 2021 through 24 June 2021
ER -