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ACDC Scribbles

Introduced by Gabriele Valvano et al. in Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates2 Jul 2020 archive 2025-07-28

We release expert-made scribble annotations for the medical ACDC dataset [1]. The released data must be considered as extending the original ACDC dataset. The ACDC dataset contains cardiac MRI images, paired with hand-made segmentation masks. It is possible to use the segmentation masks provided in the ACDC dataset to evaluate the performance of methods trained using only scribble supervision.

References: [1] Bernard, Olivier, et al. "Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?." IEEE transactions on medical imaging 37.11 (2018): 2514-2525.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Semantic Segmentation ACDC Scribbles ScribFormer Dice (Average) 88.8% ScribFormer: Transformer Makes CNN Work Better for... HUANGLIZI/ScribFormer 6 Compare

Papers archive 2025-07-28

6 shown of 6 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 10. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

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Tasks archive 2025-07-28

License archive 2025-07-28

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Modalities archive 2025-07-28

Languages archive 2025-07-28

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Variants archive 2025-07-28

  • ACDC Scribbles

1 variant name, as the archive lists them.

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