Journal
Frontiers in Oncology
Publication Date
1-1-2022
Volume
12
First Page
1007874
Document Type
Open Access Publication
DOI
10.3389/fonc.2022.1007874
Rights and Permissions
Leal JP, Rowe SP, Stearns V, Connolly RM, Vaklavas C, Liu MC, Storniolo AM, Wahl RL, Pomper MG and Solnes LB (2022) Automated lesion detection of breast cancer in [18F] FDG PET/CT using a novel AI-Based workflow. Front. Oncol. 12:1007874. doi: 10.3389/fonc.2022.1007874 © 2022 Leal, Rowe, Stearns, Connolly, Vaklavas, Liu, Storniolo, Wahl, Pomper and Solnes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Recommended Citation
Leal, Jeffrey P; Rowe, Steven P; Stearns, Vered; Connolly, Roisin M; Vaklavas, Christos; Liu, Minetta C; Storniolo, Anna Maria; Wahl, Richard L; Pomper, Martin G; and Solnes, Lilja B, "Automated lesion detection of breast cancer in [18F] FDG PET/CT using a novel AI-Based workflow." Frontiers in Oncology. 12, 1007874 (2022).
https://digitalcommons.wustl.edu/oa_4/1859
