48 citations · 57 across the 3 of their papers we have counts for
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eess.IV2022★ 9 cited
On the in vivo recognition of kidney stones using machine learning
Francisco Lopez-Tiro, Vincent Estrade, Jacques Hubert +4
Determining the type of kidney stones allows urologists to prescribe a treatment to avoid recurrence of renal lithiasis. An automated in-vivo image-based classification method woul…
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…