Automated segmentation is an important step in automated processing of radiographs. However, manual generation of training data is tedious. To overcome this challenge, we leverage synthetic radiograph training data generated from CT volumes together with corresponding anatomy segmentation labels. We demonstrate the effectiveness of this approach on the use case of automated scoliosis Cobb angle quantification. Read More

Meeting name: SPR 2025 Annual Meeting , 2025

Authors: Vasanawala Sauram, Pauly John, Gatidis Sergios

Keywords: Segmentation, Scoliosis, Deep Learning