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Models/VF-CNN (C12)

VF-CNN (C12)

Reported on 6 benchmarks across 3 tasks · 1 paper · 2 SOTA

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

Medical8 results

Multi-tissue Nucleus SegmentationonKumar
Dice· 2016-12-29
0.813
best: 0.843 (GC-MHVN)
SOTA
Rotation equivariant vector field networks arXiv:1612.09346
Multi-tissue Nucleus SegmentationonKumar
Hausdorff Distance (mm)· 2016-12-29
51.4
best: 60 (DSF-CNN (C8))
SOTA
Rotation equivariant vector field networks arXiv:1612.09346
Breast Tumour ClassificationonPCam
AUC· 2016-12-29
0.898
best: 0.975 (DSF-CNN (C8))
Rotation equivariant vector field networks arXiv:1612.09346
Colorectal Gland Segmentation:onCRAG
Dice· 2016-12-29
0.782
best: 0.892 (PatchCL)
Rotation equivariant vector field networks arXiv:1612.09346
Colorectal Gland Segmentation:onCRAG
F1-score· 2016-12-29
0.776
best: 0.881 (PatchCL)
Rotation equivariant vector field networks arXiv:1612.09346
Colorectal Gland Segmentation:onCRAG
Hausdorff Distance (mm)· 2016-12-29
251.9
best: 318.9 (VF-CNN (C4))
Rotation equivariant vector field networks arXiv:1612.09346
Multi-tissue Nucleus SegmentationonKumar
Dice· 2016-12-29
0.808
best: 0.843 (GC-MHVN)
Rotation equivariant vector field networks arXiv:1612.09346
Multi-tissue Nucleus SegmentationonKumar
Hausdorff Distance (mm)· 2016-12-29
50.7
best: 60 (DSF-CNN (C8))
Rotation equivariant vector field networks arXiv:1612.09346