1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2023
Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations
Daniel Flores-Araiza, Francisco Lopez-Tiro, Jonathan El-Beze +4
Identifying the type of kidney stones can allow urologists to determine their cause of formation, improving the prescription of appropriate treatments to diminish future relapses.…
cs.CV2022★ 1 cited
Improved Kidney Stone Recognition Through Attention and Multi-View Feature Fusion Strategies
Elias Villalvazo-Avila, Francisco Lopez-Tiro, Jonathan El-Beze +4
This contribution presents a deep learning method for the extraction and fusion of information relating to kidney stone fragments acquired from different viewpoints of the endoscop…