A multi‐scale network for thyroid segmentation and dose assessment in hyperthyroid patients with uncertainty quantification

The proposed MSRA-UNet++ network provides segmentation results with estimated uncertainty and higher accuracy. The reliability of S values was enhanced by combining segmentation uncertainty with Monte Carlo simulations. To the best of our knowledge, this study is the first to introduce an uncertainty quantification module into the CT image segmentation process for hyperthyroid patients. Additionally, it combines patient-specific thyroid voxel phantoms with individualized radioiodine kinetics data to assess the absorbed dose using the MIRD schema, with the results compared to the Marinelli-Quimby formula. The code will be release on https://github.com/410435553.