Implementation of a Commercial Deep Learning-Based Auto Segmentation Software in Radiotherapy: Evaluation of Effectiveness and Impact on Workflow

Keyphrases

• Radiotherapy 100%
• Radiation Therapy 100%
• Effectiveness Evaluation 100%
• Impact Evaluation 100%
• Organs at Risk 100%
• Automatic Segmentation 100%
• Limbus 100%
• Segmentation Tool 100%
• Deep-learning-based Auto-segmentation 100%
• Head-and-neck 50%
• Lung 50%
• Rectum 50%
• Center of Mass 50%
• Head-and-neck Cancer 50%
• Disease-specific 50%
• Colorectal Cancer 50%
• Bladder 50%
• Breast 50%
• Cancer Cases 50%
• Canada 50%
• Medical Doctors 50%
• Prostate 50%
• Interobserver Variability 50%
• Site of Disease 50%
• Time Reduction 50%
• Commercial Software 50%
• Efficiency Improvement 50%
• Mass Shift 50%
• Isodose 50%
• Volume Variation 50%
• Dosimetric Differences 50%
• Manual Segmentation 50%
• U-Net 50%
• Femoral Head 50%
• Deep Convolutional Neural Network (deep CNN) 50%
• Dosimetric Impact 50%
• Shift Impact 50%
• Radiotherapy Workflow 50%
• Software Use 50%
• Automatic Contouring 50%
• Manual Contouring 50%
• Dice Similarity 50%
• Auto-contouring 50%

Medicine and Dentistry

• Radiation Therapy 100%
• Contouring 100%
• Disease 50%
• Corneal Limbus 50%
• Neck 25%
• Head and Neck Cancer 25%
• Rectum Cancer 25%
• Physician 25%
• Bladder 25%
• Femoral Head 25%
• Lung 25%