Bone marrow fat fraction (BMFF) has been recognized as one of the quantitative image biomarkers to identify abnormal bone density using modified Dixon sequence. However, this method requires manual segmentation which limits its adoption in clinical practice. In this study, we developed a fully automated radiomics pipeline using deep learning based segmentation and validated its performance comparable to manual segmentation. This finding will facilitate the clinical utility of the entire pipeline as a screening tool for early detection of abnormal bone density.
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