In a head-to-head benchmark on three public MRI datasets, MRSegmentator was the most accurate and generalizable abdominal multi-organ segmentation tool, and ABDSynth, trained only on CT segmentations, proved a viable low-annotation alternative.
N a- tional cancer institute imaging data commons: Toward trans parency, reproducibility, and scalability in imaging artificial int elligence,
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Benchmarking of Deep Learning Methods for Generic MRI Multi-Organ Abdominal Segmentation
In a head-to-head benchmark on three public MRI datasets, MRSegmentator was the most accurate and generalizable abdominal multi-organ segmentation tool, and ABDSynth, trained only on CT segmentations, proved a viable low-annotation alternative.