2 citations · 8 across the 9 of their papers we have counts for
9 papers
Evaluating the plausibility of synthetic images for improving automated endoscopic stone recognition
Ruben Gonzalez-Perez, Francisco Lopez-Tiro, Ivan Reyes-Amezcua +6
Currently, the Morpho-Constitutional Analysis (MCA) is the de facto approach for the etiological diagnosis of kidney stone formation, and it is an important step for establishing p…
A metric learning approach for endoscopic kidney stone identification
Jorge Gonzalez-Zapata, Francisco Lopez-Tiro, Elias Villalvazo-Avila +5
Several Deep Learning (DL) methods have recently been proposed for an automated identification of kidney stones during an ureteroscopy to enable rapid therapeutic decisions. Even i…
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.…
Improving automatic endoscopic stone recognition using a multi-view fusion approach enhanced with two-step transfer learning
Francisco Lopez-Tiro, Elias Villalvazo-Avila, Juan Pablo Betancur-Rengifo +4
This contribution presents a deep-learning method for extracting and fusing image information acquired from different viewpoints, with the aim to produce more discriminant object f…
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…
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning
Francisco Lopez-Tiro, Juan Pablo Betancur-Rengifo, Arturo Ruiz-Sanchez +6
Knowing the cause of kidney stone formation is crucial to establish treatments that prevent recurrence. There are currently different approaches for determining the kidney stone ty…
Interpretable Deep Learning Classifier by Detection of Prototypical Parts on Kidney Stones Images
Daniel Flores-Araiza, Francisco Lopez-Tiro, Elias Villalvazo-Avila +4
Identifying the type of kidney stones can allow urologists to determine their formation cause, improving the early prescription of appropriate treatments to diminish future relapse…
Comparing feature fusion strategies for Deep Learning-based kidney stone identification
Elias Villalvazo-Avila, Francisco Lopez-Tiro, Daniel Flores-Araiza +4
This contribution presents a deep-learning method for extracting and fusing image information acquired from different viewpoints with the aim to produce more discriminant object fe…
On the generalization capabilities of FSL methods through domain adaptation: a case study in endoscopic kidney stone image classification
Mauricio Mendez-Ruiz, Francisco Lopez-Tiro, Jonathan El-Beze +5
Deep learning has shown great promise in diverse areas of computer vision, such as image classification, object detection and semantic segmentation, among many others. However, as…