Zobrazeno 1 - 10
of 131
pro vyhledávání: '"Ochoa Ruiz, Gilberto"'
Evaluating the plausibility of synthetic images for improving automated endoscopic stone recognition
Autor:
Gonzalez-Perez, Ruben, Lopez-Tiro, Francisco, Reyes-Amezcua, Ivan, Falcon-Morales, Eduardo, Rodriguez-Gueant, Rosa-Maria, Hubert, Jacques, Daudon, Michel, Ochoa-Ruiz, Gilberto, Daul, Christian
Publikováno v:
2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS)
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 personalized treatment to avoid relapses. More recently, research has f
Externí odkaz:
http://arxiv.org/abs/2409.13409
Autor:
Flores-Araiza, Daniel, Lopez-Tiro, Francisco, Larose, Clément, Hinojosa, Salvador, Mendez-Vazquez, Andres, Gonzalez-Mendoza, Miguel, Ochoa-Ruiz, Gilberto, Daul, Christian
The in-vivo identification of the kidney stone types during an ureteroscopy would be a major medical advance in urology, as it could reduce the time of the tedious renal calculi extraction process, while diminishing infection risks. Furthermore, such
Externí odkaz:
http://arxiv.org/abs/2409.12883
Publikováno v:
2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS)
Frequent monitoring is necessary to stratify individuals based on their likelihood of developing gastrointestinal (GI) cancer precursors. In clinical practice, white-light imaging (WLI) and complementary modalities such as narrow-band imaging (NBI) a
Externí odkaz:
http://arxiv.org/abs/2409.12450
Autor:
Quihui-Rubio, Pablo Cesar, Flores-Araiza, Daniel, Gonzalez-Mendoza, Miguel, Mata, Christian, Ochoa-Ruiz, Gilberto
This contribution presents a deep learning method for the segmentation of prostate zones in MRI images based on U-Net using additive and feature pyramid attention modules, which can improve the workflow of prostate cancer detection and diagnosis. The
Externí odkaz:
http://arxiv.org/abs/2309.01322
Autor:
Guarduño-Martinez, Eduardo, Ciprian-Sanchez, Jorge, Valente, Gerardo, Vazquez-Garcia, Rodriguez-Hernandez, Gerardo, Palacios-Rosas, Adriana, Rossi-Tisson, Lucile, Ochoa-Ruiz, Gilberto
Wildfires represent one of the most relevant natural disasters worldwide, due to their impact on various societal and environmental levels. Thus, a significant amount of research has been carried out to investigate and apply computer vision technique
Externí odkaz:
http://arxiv.org/abs/2309.01318
Autor:
Quihui-Rubio, Pablo Cesar, Flores-Araiza, Daniel, Ochoa-Ruiz, Gilberto, Gonzalez-Mendoza, Miguel, Mata, Christian
This study focuses on comparing deep learning methods for the segmentation and quantification of uncertainty in prostate segmentation from MRI images. The aim is to improve the workflow of prostate cancer detection and diagnosis. Seven different U-Ne
Externí odkaz:
http://arxiv.org/abs/2308.04653
Autor:
Gonzalez-Zapata, Jorge, Lopez-Tiro, Francisco, Villalvazo-Avila, Elias, Flores-Araiza, Daniel, Hubert, Jacques, Mendez-Vazquez, Andres, Ochoa-Ruiz, Gilberto, Daul, Christian
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 if these DL approaches led to promising results, they are mainly approp
Externí odkaz:
http://arxiv.org/abs/2307.07046
Autor:
Mendez-Ruiz, Mauricio, Gonzalez-Zapata, Jorge, Reyes-Amezcua, Ivan, Flores-Araiza, Daniel, Lopez-Tiro, Francisco, Mendez-Vazquez, Andres, Ochoa-Ruiz, Gilberto
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 leverage the meta-learning approach, which is encompassed by episodic tasks
Externí odkaz:
http://arxiv.org/abs/2305.09062
Sign Language Recognition (SLR) systems aim to be embedded in video stream platforms to recognize the sign performed in front of a camera. SLR research has taken advantage of recent advances in pose estimation models to use skeleton sequences estimat
Externí odkaz:
http://arxiv.org/abs/2304.05403
Autor:
Flores-Araiza, Daniel, Lopez-Tiro, Francisco, El-Beze, Jonathan, Hubert, Jacques, Gonzalez-Mendoza, Miguel, Ochoa-Ruiz, Gilberto, Daul, Christian
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. Currently, the associated ex-vivo diagnosis (known as Morpho-constitut
Externí odkaz:
http://arxiv.org/abs/2304.04077