TY - GEN
T1 - Sparse Non-Negative Matrix Factorization for Preclinical Bioluminescent Imaging
AU - Dereure, Erwan
AU - Kervazo, Christophe
AU - Seguin, Johanne
AU - Garofalakis, Anikitos
AU - Mignet, Nathalie
AU - Angelini, Elsa
AU - Olivo-Marin, Jean Christophe
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Bioluminescent imaging is used in oncology to measure tumoral size and activity via spatio-temporal photon emission counting. Bioluminescent signal analysis often requires delineating regions of interest around each tumor by hand, which complicates quantification in the case of mice bearing multiple tumors. In this work, we propose to use Non-Negative Matrix Factorization with data-adaptive sparsity constraints to enable automated separation of signals emitted from multiple tumors in mice. Results are presented on a set of 18 long-exposure acquisitions.
AB - Bioluminescent imaging is used in oncology to measure tumoral size and activity via spatio-temporal photon emission counting. Bioluminescent signal analysis often requires delineating regions of interest around each tumor by hand, which complicates quantification in the case of mice bearing multiple tumors. In this work, we propose to use Non-Negative Matrix Factorization with data-adaptive sparsity constraints to enable automated separation of signals emitted from multiple tumors in mice. Results are presented on a set of 18 long-exposure acquisitions.
KW - Bioluminescent Imaging
KW - Blind Source Separation
KW - Oncology
KW - Optimization
KW - Preclinical imaging
UR - https://www.scopus.com/pages/publications/85172090094
U2 - 10.1109/ISBI53787.2023.10230751
DO - 10.1109/ISBI53787.2023.10230751
M3 - Conference contribution
AN - SCOPUS:85172090094
T3 - Proceedings - International Symposium on Biomedical Imaging
BT - 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023
PB - IEEE Computer Society
T2 - 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023
Y2 - 18 April 2023 through 21 April 2023
ER -