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Models/ResU-Net

ResU-Net

Reported on 8 benchmarks across 2 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical8 results

  • Medical Image SegmentationonROSE-2
    Dice Score· 2017-11-29
    67.25
    best: 71.18 (OCTAve: OCTA-Net)
    SOTA
    Road Extraction by Deep Residual U-NetarXiv:1711.10684
  • Medical Image SegmentationonROSE-1 SVC-DVC
    Dice Score· 2017-11-29
    74.61
    best: 81.42 (OCTAve: OCTA-Net)
    SOTA
    Road Extraction by Deep Residual U-NetarXiv:1711.10684
  • Medical Image SegmentationonROSE-1 SVC
    Dice Score· 2017-11-29
    74.61
    best: 78.03 (OCTAve: OCTA-Net)
    SOTA
    Road Extraction by Deep Residual U-NetarXiv:1711.10684
  • Retinal Vessel SegmentationonROSE-2
    Dice Score· 2017-11-29
    67.25
    best: 71.18 (OCTAve: OCTA-Net)
    SOTA
    Road Extraction by Deep Residual U-NetarXiv:1711.10684
  • Retinal Vessel SegmentationonROSE-1 SVC-DVC
    Dice Score· 2017-11-29
    74.61
    best: 81.42 (OCTAve: OCTA-Net)
    SOTA
    Road Extraction by Deep Residual U-NetarXiv:1711.10684
  • Retinal Vessel SegmentationonROSE-1 SVC
    Dice Score· 2017-11-29
    74.61
    best: 78.03 (OCTAve: OCTA-Net)
    SOTA
    Road Extraction by Deep Residual U-NetarXiv:1711.10684
  • Medical Image SegmentationonROSE-1 DVC
    Dice Score· 2017-11-29
    65.67
    best: 70.74 (OCTA-Net)
    Road Extraction by Deep Residual U-NetarXiv:1711.10684
  • Retinal Vessel SegmentationonROSE-1 DVC
    Dice Score· 2017-11-29
    65.67
    best: 70.74 (OCTA-Net)
    Road Extraction by Deep Residual U-NetarXiv:1711.10684