Congress:
ECR25
Poster Number:
C-14717
Type:
Poster: EPOS Radiologist (scientific)
Authorblock:
A. Olesinski, R. Lederman, J. Sosna, L. Joskowicz; Jerusalem/IL
Disclosures:
Alon Olesinski:
Consultant: HighRAD
Richard Lederman:
Consultant: HighRAD
Jacob Sosna:
Consultant: HighRAD
Leo Joskowicz:
Consultant: HighRAD and Ezra
Keywords:
Artificial Intelligence, Lymph nodes, Oncology, CT, CAD, Computer Applications-Detection, diagnosis, Cancer
1. Mountain CF, Dresler CM. 1997. Regional lymph node classification for lung cancer staging. Chest 111(6):1718-23.
2. Schwartz LH, Bogaerts J, Ford R, Shankar L, Therasse P, Gwyther S, Eisenhauer EA. 2009. Evaluation of lymph nodes with RECIST 1.1. European J. Cancer 45(2):261-7.
3. Isensee F, Jaeger PF, Kohl SA, Petersen J, Maier-Hein KH. 2021. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature Methods 18(2):203-11.
4. Wasserthal J, Breit HC, Meyer MT, Pradella M, Hinck D, Sauter AW, Heye T, Boll DT, Cyriac J, Yang S, Bach M. 2023. TotalSegmentator: robust segmentation of 104 anatomic structures in CT images. Radiology: Artificial Intelligence 5(5).