Unsupervised statistical segmentation of multispectral volumetric MRI images. - José Gerardo Tamez-Peña; Saara M. S. Totterman; Kevin J. Parker (Image Processing, 1999)

Automated Measurement of Structures on CT and MR Imagery: A Validation Study. - Edward A. Ashton; Saara M. S. Totterman; Chihiro Takahashi; José G. Tamez-Peña; Kevin J. Parker (CBMS, 2001)

MRI isotropic resolution reconstruction from two orthogonal scans. - José Gerardo Tamez-Peña; Saara M. S. Totterman; Kevin J. Parker (Image Processing, 2001)

Segmentation, surface extraction, and thickness computation of articular cartilage. - S. Kubilay Pakin; José Gerardo Tamez-Peña; Saara M. S. Totterman; Kevin J. Parker (Image Processing, 2002)

Focal Cartilage Defect Progression Detection: Measurement of Precision and Variation in Natural Characteristics of Cartilage Thickness Maps Derived from 3D MRI Data. - Monica Barbu-McInnis; José G. Tamez-Peña; Saara M. S. Totterman (ISBI, 2004)

Knee cartilage extraction and bone-cartilage interface analysis from 3D MRI data sets. - José Gerardo Tamez-Peña; Monica Barbu-McInnis; Saara M. S. Totterman (Image Processing, 2004)

Unsupervised definition of the tibia-femoral joint regions of the human knee and its applications to cartilage analysis. - José Gerardo Tamez-Peña; Monica Barbu-McInnis; Saara M. S. Totterman (Image Processing, 2006)

Segmentation by surface-to-image registration. - Zhiyong Xie; José G. Tamez-Peña; Michael A. Gieseg; Serguei Liachenko; Shantanu Dhamija; Ping Chiao (Image Processing, 2006)

Structural quantification of cartilage changes using statistical parametric mapping. - José Gerardo Tamez-Peña; Monica Barbu-McInnis; Saara M. S. Totterman (Image Processing, 2007)

Atlas based method for the automated segmentation and quantification of knee features: Data from the osteoarthritis initiative. - José G. Tamez-Peña; Patricia C. González; Joshua Farber; Karl G. Baum; Eduard Schreyer; Saara M. S. Totterman (ISBI, 2011)

COMPADRE: an R and web resource for pathway activity analysis by component decompositions. - Roberto-Rafael Ramos-Rodriguez; Raquel Cuevas-Diaz-Duran; Francesco Falciani; José Gerardo Tamez-Peña; Victor Trevino (Bioinform., 2012)

Unsupervised Segmentation and Quantification of Anatomical Knee Features: Data From the Osteoarthritis Initiative. - José G. Tamez-Peña; Joshua Farber; Patricia C. González; Eduard Schreyer; Erika Schneider; Saara M. S. Totterman (IEEE Trans. Biomed. Eng., 2012)

Improved multimodal biomarkers for Alzheimer's disease and mild cognitive impairment diagnosis: data from ADNI. - Antonio Martínez-Torteya; Victor Treviño-Alvarado; José G. Tamez-Peña (Computer-Aided Diagnosis, 2013)

Predictive features of breast cancer on Mexican screening mammography patients. - Juan Rodríguez-Rojas; Margarita Garza-Montemayor; Victor Treviño-Alvarado; José Gerardo Tamez-Peña (Computer-Aided Diagnosis, 2013)

Local image registration a comparison for bilateral registration mammography. - José M. Celaya-Padilla; Juan Rodríguez-Rojas; Victor Trevino; José Gerardo Tamez-Peña (CoRR, 2013)

Knee Osteoarthritis pain prediction from X-ray imaging: Data from Osteoarthritis Initiative. - Jorge I. Galván-Tejada; Victor Trevino; José M. Celaya-Padilla; José G. Tamez-Peña (CONIELECOMP, 2014)

Radiological Pain Predictors in Knee Osteoarthritis, a Four Feature Selection Comparison: Data from the OAI. - Jorge I. Galván-Tejada; José M. Celaya-Padilla; Carlos Eric Galván-Tejada; Victor Trevino; José G. Tamez-Peña (MCPR, 2014)

Bilateral image subtraction features for multivariate automated classification of breast cancer risk. - José M. Celaya-Padilla; Juan Rodríguez-Rojas; Jorge I. Galván-Tejada; Antonio Martínez-Torteya; Victor Treviño; José G. Tamez-Peña (Computer-Aided Diagnosis, 2014)

Wide association study of radiological features that predict future knee OA pain: data from the OAI. - Jorge I. Galván-Tejada; José M. Celaya-Padilla; Antonio Martínez-Torteya; Juan Rodríguez-Rojas; Victor Treviño; José G. Tamez-Peña (Computer-Aided Diagnosis, 2014)

MRI signal and texture features for the prediction of MCI to Alzheimer's disease progression. - Antonio Martínez-Torteya; Juan Rodríguez-Rojas; José M. Celaya-Padilla; Jorge I. Galván-Tejada; Victor Treviño; José G. Tamez-Peña (Computer-Aided Diagnosis, 2014)

Knee osteoarthritis image registration: data from the Osteoarthritis Initiative. - Jorge I. Galván-Tejada; José M. Celaya-Padilla; Victor Treviño; José G. Tamez-Peña (Computer-Aided Diagnosis, 2015)

Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI. - Jorge I. Galván-Tejada; José M. Celaya-Padilla; Victor Trevino; José Gerardo Tamez-Peña (Comput. Math. Methods Medicine, 2015)

On the Use of Coupled Shape Priors for Segmentation of Magnetic Resonance Images of the Knee. - Jincheng Pang; Jeffrey B. Driban; Timothy E. McAlindon; José G. Tamez-Peña; Jurgen Fripp; Eric L. Miller 001 (IEEE J. Biomed. Health Informatics, 2015)

Scan-rescan precision of subchondral bone curvature maps from routine 3D DESS water excitation sequences: Data from the Osteoarthritis Initiative. - Joshua Farber; Saara M. S. Totterman; Antonio Martínez-Torteya; José G. Tamez-Peña (Comput. Biol. Medicine, 2016)

VALORATE: fast and accurate log-rank test in balanced and unbalanced comparisons of survival curves and cancer genomics. - Victor Trevino; José G. Tamez-Peña (Bioinform., 2017)

Longitudinal gender-specific differences in the conversion from mild cognitive impairment to Alzheimer's disease. - Angel G. Cadena-Hernandez; Alejandro I. Trejo-Castro; José M. Celaya-Padilla; José G. Tamez-Peña; Antonio Martínez-Torteya (BHI, 2018)

Differences in the Progression from Mild Cognitive Impairment to Alzheimer's Disease between APOE4 Carriers and Non-Carriers. - Antonio Martínez-Torteya; Alejandro I. Trejo-Castro; José M. Celaya-Padilla; José G. Tamez-Peña (BIBE, 2019)

Measuring hippocampal neuroanatomical asymmetry to better diagnose Alzheimer's disease. - Antonio Martínez-Torteya; Félix E. Rodríguez-Cantú; Mónica Rivera-Dávila; José M. Celaya-Padilla; José G. Tamez-Peña (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI. - José G. Tamez-Peña; Jorge Orozco; Patricia Sosa; Alejandro Valdes; Fahimeh Nezhadmoghadam (ABCD-NP@MICCAI, 2019)

Benchmarking machine learning models for late-onset alzheimer's disease prediction from genomic data. - Javier De Velasco Oriol; Edgar E. Vallejo-Clemente; Karol Estrada; José Gerardo Tamez-Peña; Alzheimer's Disease Neuroimaging Initiative (BMC Bioinform., 2019)

Texture and signal features from hippocampal T2 maps as biomarkers for MCI to AD progression. - 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 (BIBM, 2020)

Prediction of MCI to AD risk of conversion survival models: qMRI vs CSF measures and cognitive assessments. - Jorge Orozco-Sanchez; José G. Tamez-Peña (Computer-Aided Diagnosis, 2020)

COVID-19 classification using thermal images: thermal images capability for identifying COVID-19 using traditional machine learning classifiers. - Martha Rebeca Canales-Fiscal; Rocío Ortiz López; Regina Barzilay; Victor Treviño; Servando Cardona-Huerta; Luis Javier Ramírez-Treviño; Adam Yala; José G. Tamez-Peña (BCB, 2021)

Risk profiles for negative and positive COVID-19 hospitalized patients. - Fahimeh Nezhadmoghadam; José G. Tamez-Peña (Comput. Biol. Medicine, 2021)

Unsupervised discovery of Mild Cognitive Impairment subtypes of Alzheimer's disease using consensus clustering and unsupervised learning techniques. - Fahimeh Nezhadmoghadam; José Gerardo Tamez-Peña (ICBRA, 2022)

Glaucoma classification using a morphological-convolutional neural network trained with extreme learning machine. - Martha Rebeca Canales-Fiscal; José Gerardo Tamez-Peña (Computer-Aided Diagnosis, 2023)

Hybrid morphological-convolutional neural networks for computer-aided diagnosis. - Martha Rebeca Canales-Fiscal; José Gerardo Tamez-Peña (Frontiers Artif. Intell., 2023)

Deep learning, radiomics and radiogenomics applications in the digital breast tomosynthesis: a systematic review. - Sadam Hussain; Yareth Lafarga-Osuna; Mansoor Ali; Usman Naseem; Masroor Ahmed; José Gerardo Tamez-Peña (BMC Bioinform., 2023)

Named Entity Recognition in Mammography Radiology Reports using a Multilingual Transfer Learning Approach. - Esteban Ricardo Salazar Cabrera; Alejandro Santos-Díaz; Ernestina Menasalvas; José Gerardo Tamez-Peña; Victor Robles (CBMS, 2024)

Performance Evaluation of Deep Learning and Transformer Models Using Multimodal Data for Breast Cancer Classification. - 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 Gerardo Tamez-Peña (CaPTion@MICCAI, 2024)

FRESA.CAD::ILAA: Estimating the exploratory residualization transform. - José Gerardo Tamez-Peña (SoftwareX, 2024)

Ensemble of Radiomics and Convnext for Breast Cancer Diagnosis. - Jorge Alberto Garza Abdala; Gerardo Alejandro Fumagal-González; Beatriz Alejandra Bosques Palomo; Mario Alexis Monsivais Molina; Daly Avedano; Servando Cardona-Huerta; José Gerardo Tamez-Peña (CBMS, 2025)

Assessing a Proposed Dynamic Ratio in Dataset Class Imbalance with GAN's Generated Melanoma Images. - Gerardo Alejandro Fumagal-González; Jorge Alberto Garza Abdala; Alma Alhelí Pedro Pérez; José Gerardo Tamez-Peña (CBMS, 2025)

Comparison of ConvNeXt and Vision-Language Models for Breast Density Assessment in Screening Mammography. - Yusdivia Molina-Román; David Gómez-Ortiz; Ernestina Menasalvas Ruiz; José Gerardo Tamez-Peña; Alejandro Santos-Díaz (CBMS, 2025)

Multiview Multimodal Feature Fusion for Breast Cancer Classification Using Deep Learning. - Sadam Hussain; Mansoor Ali Teevno; Usman Naseem; Daly Betzabeth Avendano Avalos; Servando Cardona-Huerta; José Gerardo Tamez-Peña (IEEE Access, 2025)