CT Image Standardization Using Deep Image Synthesis Models
Md. Selim, Jie Zhang, Jin Chen · 2023
Radiomics is a growing field for quantitative image analysis, but the lack of imaging standards hinders the progress of radiomics in large-scale cancer studies. Radiomic features are turned to bias to the scanners or the acquisition protocols used. High-quality image standardization is crucial for the advancement of radiomics. The recently developed deep learning-based image synthesis models show prominence in CT image standardization. This review introduces the development and evaluation of deep image synthesis-based CT image standardization models for generating reliable radiomic features.