output
20162026
most citedAssessing deep learning methods for the identification of kidney stones in endoscopic images

48 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing 2021Show all

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eess.IV2021★ 48 cited

Assessing deep learning methods for the identification of kidney stones in endoscopic images

Francisco Lopez, Andres Varela, Oscar Hinojosa +8

Knowing the type (i.e., the biochemical composition) of kidney stones is crucial to prevent relapses with an appropriate treatment. During ureteroscopies, kidney stones are fragmen…