Dice similarity coefficient

Last revised by Daniel J Bell on 2 Aug 2021

Citation, DOI, disclosures and article data

Citation:

Moore C, Bell D, Dice similarity coefficient. Reference article, Radiopaedia.org (Accessed on 16 Apr 2024) https://doi.org/10.53347/rID-75056

DOI:

https://doi.org/10.53347/rID-75056

Permalink:

https://radiopaedia.org/articles/75056

rID:

75056

Article created:

15 Mar 2020, Candace Makeda Moore

Disclosures:

At the time the article was created Candace Makeda Moore had no recorded disclosures.

View Candace Makeda Moore's current disclosures

Last revised:

2 Aug 2021, Daniel J Bell ◉

Disclosures:

At the time the article was last revised Daniel J Bell had no recorded disclosures.

View Daniel J Bell's current disclosures

Revisions:

4 times, by 2 contributors - see full revision history and disclosures

Sections:

Artificial Intelligence

Synonyms:

Sørensen–Dice index
Sorensen–Dice index
Dice coefficient
Dice coefficients

The Dice similarity coefficient, also known as the Sørensen–Dice index or simply Dice coefficient, is a statistical tool which measures the similarity between two sets of data. This index has become arguably the most broadly used tool in the validation of image segmentation algorithms created with AI, but it is a much more general concept which can be applied to sets of data for a variety of applications including NLP.

The equation for this concept is:
2 * |X ∩ Y| / (|X| + |Y|)

where X and Y are two sets
a set with vertical bars either side refers to the cardinality of the set, i.e. the number of elements in that set, e.g. |X| means the number of elements in set X
∩ is used to represent the intersection of two sets, and means the elements that are common to both sets