Performance Evaluation of a Deep Learning System for Differential Diagnosis of Lung Cancer With Conventional CT and FDG PET/CT Using Transfer Learning and Metadata.

Journal: Clinical nuclear medicine

Published Date: Aug 1, 2021

Abstract

PURPOSE: We aimed to evaluate the performance of a deep learning system for differential diagnosis of lung cancer with conventional CT and FDG PET/CT using transfer learning (TL) and metadata.

Authors

Yong-Jin Park
Dongmin Choi

Department of Computer Science, Yonsei University, Seoul, South Korea.
Joon Young Choi

From the Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul.
Seung Hyup Hyun

From the Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul.

Keywords

Aged Deep Learning Diagnosis, Differential Fluorodeoxyglucose F18 Humans Image Processing, Computer-Assisted Lung Neoplasms Male Metadata Middle Aged Positron Emission Tomography Computed Tomography Retrospective Studies ROC Curve

External Resources

View on PubMed Access via DOI PubMed (33883488)

Performance Evaluation of a Deep Learning System for Differential Diagnosis of Lung Cancer With Conventional CT and FDG PET/CT Using Transfer Learning and Metadata.

Abstract

Authors

Keywords

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