Methods › General › Loss Functions › Dice Loss

Dice Loss

108 papers tagged archive 2025-07-28

Introduced by Carole H. Sudre et al. in Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

DiceLoss( y, p ) = 1 - ( 2yp + 1 ) ( y+p + 1 )

PaperSource

Papers archive 2025-07-28

30 shown of 108, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 96 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Segmentation58
Semantic Segmentation43
Image Segmentation28
Medical Image Segmentation17
Tumor Segmentation13
Decoder11
Brain Tumor Segmentation9
Computed Tomography (CT)5
Data Augmentation5
Deep Learning5
Lesion Segmentation5
Anatomy4
Specificity4
Boundary Detection3
Diagnostic3
General Classification3
Medical Image Analysis3
Survival Prediction3
Anomaly Detection2
Attribute2

Usage over time archive 2025-07-28

Papers per year tagged with Dice Loss: 2017 to 2025, peak 19 19 0 2017: 1 paper 2017 2018: 9 papers 2018 2019: 18 papers 2019 2020: 19 papers 2020 2021: 12 papers 2021 2022: 18 papers 2022 2023: 11 papers 2023 2024: 9 papers 2024 2025: 11 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (108 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Loss Functions

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