4 citations · 16 across the 26 of their papers we have counts for
6 papers · 1 filter
Causal Scoring Medical Image Explanations: A Case Study On Ex-vivo Kidney Stone Images
Armando Villegas-Jimenez, Daniel Flores-Araiza, Francisco Lopez-Tiro +1
On the promise that if human users know the cause of an output, it would enable them to grasp the process responsible for the output, and hence provide understanding, many explaina…
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…
SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification
Mauricio Mendez-Ruiz, Jorge Gonzalez-Zapata, Ivan Reyes-Amezcua +4
Few-shot learning is a challenging area of research that aims to learn new concepts with only a few labeled samples of data. Recent works based on metric-learning approaches levera…
Deep learning-based image exposure enhancement as a pre-processing for an accurate 3D colon surface reconstruction
Ricardo Espinosa, Carlos Axel Garcia-Vega, Gilberto Ochoa-Ruiz +2
This contribution shows how an appropriate image pre-processing can improve a deep-learning based 3D reconstruction of colon parts. The assumption is that, rather than global image…
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…