Automated lesion detection of breast cancer in [¹⁸F] FDG PET/CT using a novel AI-Based workflow

Keyphrases

• Breast Cancer 100%
• CT Studies 100%
• 18F-FDG PET-CT 100%
• Artificial Intelligence 100%
• Automatic Lesion Detection 100%
• Convolutional Neural Network 66%
• Positron Emission Tomography/computed Tomography (PET/CT) 66%
• Imaging Studies 33%
• Early Breast Cancer 33%
• High Specificity 33%
• Clinical Trials 33%
• Lymphadenopathy 33%
• Disease Pattern 33%
• Radiotracer 33%
• Fully Automated 33%
• Nuclear Medicine Physician 33%
• Molecular Imaging 33%
• Whole-body 33%
• Primary Lesion 33%
• Disease Identification 33%
• High Sensitivity 33%
• 18F-fluorodeoxyglucose (18F-FDG) 33%
• Multi-institutional 33%
• Quantitative Responses 33%
• Response Assessment 33%
• Tissue Type 33%
• Breast Cancer Tissues 33%
• Radiopharmaceuticals 33%
• Quantitative Detection 33%
• Medical Imaging 33%
• Automated Detection 33%
• Deep Learning 33%
• Application-oriented 33%
• Network Support 33%
• Artificial Intelligence Technology 33%
• PERCIST 33%
• Standards-based Approach 33%
• Image Processing Workflow 33%
• Jaccard Score 33%
• Traditional Image Processing 33%
• Deep Learning CNN 33%
• Artificial Intelligence/machine Learning (AI/ML) 33%
• Neural Network-based 33%
• Baseline PET 33%

Immunology and Microbiology

• Positron Emission Tomography-Computed Tomography 100%
• Artificial Intelligence 100%
• Molecular Imaging 20%
• Lymphadenopathy 20%
• Cancer Tissue 20%