José G. Tamez-Peña

24 papers B 2C 1Journal 6Unranked 15
YearRankTypeTitle / Venue / Authors
2024 J jnl
Performance Evaluation of Deep Learning and Transformer Models Using Multimodal Data for Breast Cancer Classification.
CoRR
Sadam Hussain, Mansoor Ali Teevno, Usman Naseem, Beatriz Alejandra Bosques Palomo, Mario Alexis Monsivais Molina, Jorge Alberto Garza Abdala, Daly Betzabeth Avendano Avalos, Servando Cardona-Huerta, T. Aaron Gulliver, José G. Tamez-Peña
2021 — conf
COVID-19 classification using thermal images: thermal images capability for identifying COVID-19 using traditional machine learning classifiers.
BCB
Martha Rebeca Canales-Fiscal, Rocío Ortiz López, Regina Barzilay, Victor Treviño, Servando Cardona-Huerta, Luis Javier Ramírez-Treviño, Adam Yala, José G. Tamez-Peña
2021 J jnl
Risk profiles for negative and positive COVID-19 hospitalized patients.
Comput. Biol. Medicine
Fahimeh Nezhadmoghadam, José G. Tamez-Peña
2020 — conf
Prediction of MCI to AD risk of conversion survival models: qMRI vs CSF measures and cognitive assessments.
Computer-Aided Diagnosis
Jorge Orozco-Sanchez, José G. Tamez-Peña
2020 — conf
Texture and signal features from hippocampal T2 maps as biomarkers for MCI to AD progression.
BIBM
Alejandro I. Trejo-Castro, Ricardo A. Caballero-Luna, José A. Garnica-López, Fernando Vega-Lara, José M. Celaya-Padilla, José G. Tamez-Peña, Antonio Martínez-Torteya
2019 C conf
Differences in the Progression from Mild Cognitive Impairment to Alzheimer's Disease between APOE4 Carriers and Non-Carriers.
BIBE
Antonio Martínez-Torteya, Alejandro I. Trejo-Castro, José M. Celaya-Padilla, José G. Tamez-Peña
2019 — conf
Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI.
ABCD-NP@MICCAI
José G. Tamez-Peña, Jorge Orozco, Patricia Sosa, Alejandro Valdes, Fahimeh Nezhadmoghadam
2019 — conf
Measuring hippocampal neuroanatomical asymmetry to better diagnose Alzheimer's disease.
Biomedical Applications in Molecular, Structural, and Functional Imaging
Antonio Martínez-Torteya, Félix E. Rodríguez-Cantú, Mónica Rivera-Dávila, José M. Celaya-Padilla, José G. Tamez-Peña
2018 — conf
Longitudinal gender-specific differences in the conversion from mild cognitive impairment to Alzheimer's disease.
BHI
Angel G. Cadena-Hernandez, Alejandro I. Trejo-Castro, José M. Celaya-Padilla, José G. Tamez-Peña, Antonio Martínez-Torteya
2017 J jnl
VALORATE: fast and accurate log-rank test in balanced and unbalanced comparisons of survival curves and cancer genomics.
Bioinform.
Victor Trevino, José G. Tamez-Peña
2016 J jnl
Scan-rescan precision of subchondral bone curvature maps from routine 3D DESS water excitation sequences: Data from the Osteoarthritis Initiative.
Comput. Biol. Medicine
Joshua Farber, Saara M. S. Totterman, Antonio Martínez-Torteya, José G. Tamez-Peña
2015 — conf
Knee osteoarthritis image registration: data from the Osteoarthritis Initiative.
Computer-Aided Diagnosis
Jorge I. Galván-Tejada, José M. Celaya-Padilla, Victor Treviño, José G. Tamez-Peña
2015 J jnl
On the Use of Coupled Shape Priors for Segmentation of Magnetic Resonance Images of the Knee.
IEEE J. Biomed. Health Informatics
Jincheng Pang, Jeffrey B. Driban, Timothy E. McAlindon, José G. Tamez-Peña, Jurgen Fripp, Eric L. Miller
2014 — conf
Bilateral image subtraction features for multivariate automated classification of breast cancer risk.
Computer-Aided Diagnosis
José M. Celaya-Padilla, Juan Rodríguez-Rojas, Jorge I. Galván-Tejada, Antonio Martínez-Torteya, Victor Treviño, José G. Tamez-Peña
2014 — conf
Knee Osteoarthritis pain prediction from X-ray imaging: Data from Osteoarthritis Initiative.
CONIELECOMP
Jorge I. Galván-Tejada, Victor Trevino, José M. Celaya-Padilla, José G. Tamez-Peña
2014 — conf
MRI signal and texture features for the prediction of MCI to Alzheimer's disease progression.
Computer-Aided Diagnosis
Antonio Martínez-Torteya, Juan Rodríguez-Rojas, José M. Celaya-Padilla, Jorge I. Galván-Tejada, Victor Treviño, José G. Tamez-Peña
2014 — conf
Radiological Pain Predictors in Knee Osteoarthritis, a Four Feature Selection Comparison: Data from the OAI.
MCPR
Jorge I. Galván-Tejada, José M. Celaya-Padilla, Carlos Eric Galván-Tejada, Victor Trevino, José G. Tamez-Peña
2014 — conf
Wide association study of radiological features that predict future knee OA pain: data from the OAI.
Computer-Aided Diagnosis
Jorge I. Galván-Tejada, José M. Celaya-Padilla, Antonio Martínez-Torteya, Juan Rodríguez-Rojas, Victor Treviño, José G. Tamez-Peña
2013 — conf
Improved multimodal biomarkers for Alzheimer's disease and mild cognitive impairment diagnosis: data from ADNI.
Computer-Aided Diagnosis
Antonio Martínez-Torteya, Victor Treviño-Alvarado, José G. Tamez-Peña
2012 J jnl
Unsupervised Segmentation and Quantification of Anatomical Knee Features: Data From the Osteoarthritis Initiative.
IEEE Trans. Biomed. Eng.
José G. Tamez-Peña, Joshua Farber, Patricia C. González, Eduard Schreyer, Erika Schneider, Saara M. S. Totterman
2011 — conf
Atlas based method for the automated segmentation and quantification of knee features: Data from the osteoarthritis initiative.
ISBI
José G. Tamez-Peña, Patricia C. González, Joshua Farber, Karl G. Baum, Eduard Schreyer, Saara M. S. Totterman
2006 B conf
Segmentation by surface-to-image registration.
Image Processing
Zhiyong Xie, José G. Tamez-Peña, Michael A. Gieseg, Serguei Liachenko, Shantanu Dhamija, Ping Chiao
2004 — conf
Focal Cartilage Defect Progression Detection: Measurement of Precision and Variation in Natural Characteristics of Cartilage Thickness Maps Derived from 3D MRI Data.
ISBI
Monica Barbu-McInnis, José G. Tamez-Peña, Saara M. S. Totterman
2001 B conf
Automated Measurement of Structures on CT and MR Imagery: A Validation Study.
CBMS
Edward A. Ashton, Saara M. S. Totterman, Chihiro Takahashi, José G. Tamez-Peña, Kevin J. Parker