no code implementations • 4 Sep 2023 • Pablo Cesar Quihui-Rubio, Daniel Flores-Araiza, Miguel Gonzalez-Mendoza, Christian Mata, Gilberto Ochoa-Ruiz
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.
no code implementations • 9 Aug 2023 • Pablo Cesar Quihui-Rubio, Daniel Flores-Araiza, Gilberto Ochoa-Ruiz, Miguel Gonzalez-Mendoza, Christian Mata
This study focuses on comparing deep learning methods for the segmentation and quantification of uncertainty in prostate segmentation from MRI images.
no code implementations • 19 Jul 2022 • Pablo Cesar Quihui-Rubio, Gilberto Ochoa-Ruiz, Miguel Gonzalez-Mendoza, Gerardo Rodriguez-Hernandez, Christian Mata
Prostate cancer is the second-most frequently diagnosed cancer and the sixth leading cause of cancer death in males worldwide.
no code implementations • 1 Jun 2022 • Daniela Herrera, Gilberto Ochoa-Ruiz, Miguel Gonzalez-Mendoza, Christian Mata
The best average of Hausdorff distance and mean square error were obtained using the Nested U-Net with the Dice loss function, which had an average of 6. 32 and 0. 0241 respectively.
no code implementations • 20 Jan 2022 • Carmina Pérez-Guerrero, Adriana Palacios, Gilberto Ochoa-Ruiz, Christian Mata, Joaquim Casal, Miguel Gonzalez-Mendoza, Luis Eduardo Falcón-Morales
This research work explores the application of deep learning models in an alternative approach that uses the semantic segmentation of jet fires flames to extract main geometrical attributes, relevant for fire risk assessments.
no code implementations • 7 Jul 2021 • Carmina Pérez-Guerrero, Adriana Palacios, Gilberto Ochoa-Ruiz, Christian Mata, Miguel Gonzalez-Mendoza, Luis Eduardo Falcón-Morales
One such characterization would be the segmentation of different radiation zones within the flame, so this paper presents an exploratory research regarding several traditional computer vision and Deep Learning segmentation approaches to solve this specific problem.