Profile (CV) of the research teaching staff

Journal articles

• Hernandez, Monica; Ramon Julvez, Ubaldo. Insights into traditional Large Deformation Diffeomorphic Metric Mapping and unsupervised deep-learning for diffeomorphic registration and their evaluation. COMPUTERS IN BIOLOGY AND MEDICINE. 2024. DOI: 10.1016/j.compbiomed.2024.108761
  
  
• Hernandez, Monica; Ramon-Julvez, Ubaldo; Vilades, Elisa; Cordon, Beatriz; Mayordomo, Elvira; Garcia-Martin, Elena. Explainable artificial intelligence toward usable and trustworthy computer-aided diagnosis of multiple sclerosis from Optical Coherence Tomography. PLOS ONE. 2023. DOI: 10.1371/journal.pone.0289495
  
  
• Hernández Giménez, M.; Ramón Júlvez, U.; Sierra Tomé, D. Partial Differential Equation-Constrained Diffeomorphic Registration from Sum of Squared Differences to Normalized Cross-Correlation, Normalized Gradient Fields, and Mutual Information: A Unifying Framework; 35632143. SENSORS. 2022. DOI: 10.3390/s22103735
  
  
• Hernandez, Mónica; Ramón-Julvez, Ubaldo; Ferraz, Francisco. Explainable AI toward understanding the performance of the top three TADPOLE Challenge methods in the forecast of Alzheimer’s disease diagnosis. PLOS ONE. 2022. DOI: 10.1371/journal.pone.0264695
  
  
• Hernandez, M. Efficient momentum conservation constrained PDE-LDDMM with Gauss–Newton–Krylov optimization, Semi-Lagrangian Runge–Kutta solvers, and the band-limited parameterization. JOURNAL OF COMPUTATIONAL SCIENCE. 2021. DOI: 10.1016/j.jocs.2021.101470
  
  
• Hernandez, M. Combining the Band-Limited Parameterization and Semi-Lagrangian Runge–Kutta Integration for Efficient PDE-Constrained LDDMM. JOURNAL OF MATHEMATICAL IMAGING AND VISION. 2021. DOI: 10.1007/s10851-021-01016-4
  
  
• Ramón-Júlvez, Ubaldo; Hernández, Mónica; Mayordomo, Elvira; Adni. Analysis of the influence of diffeomorphic normalization in the prediction of stable VS progressive MCI conversion with convolutional neural networks. PROCEEDINGS - INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING. 2020. DOI: 10.1109/ISBI45749.2020.9098445
  
  
• Hernandez, Monica. A Comparative Study of Different Variants of Newton-Krylov PDE-Constrained Stokes-LDDMM Parameterized in the Space of Band-Limited Vector Fields. SIAM JOURNAL ON IMAGING SCIENCES. 2019. DOI: 10.1137/18M1195310
  
  
• Hernandez, M. PDE-constrained LDDMM via geodesic shooting and inexact Gauss-Newton-Krylov optimization using the incremental adjoint Jacobi equations. PHYSICS IN MEDICINE AND BIOLOGY. 2019. DOI: 10.1088/1361-6560/aaf598
  
  
• Hernandez, M. Primal-dual optimization strategies in Huber-L1 optical flow with temporal subspace constraints for non-rigid sequence registration. IMAGE AND VISION COMPUTING. 2018. DOI: 10.1016/j.imavis.2017.11.005
  
  
• Hernandez, M. Band-Limited Stokes Large Deformation Diffeomorphic Metric Mapping. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS. 2018. DOI: 10.1109/JBHI.2018.2815346
  
  
• Hernandez, M. Primal-dual convex optimization in large deformation diffeomorphic metric mapping: LDDMM meets robust regularizers. PHYSICS IN MEDICINE AND BIOLOGY. 2017. DOI: 10.1088/1361-6560/aa925a
  
  
• Hernandez,M. Gauss-Newton inspired preconditioned optimization in large deformation diffeomorphic metric mapping. PHYSICS IN MEDICINE AND BIOLOGY. 2014. DOI: 10.1088/0031-9155/59/20/6085
  
  
• Serrano Tierz, Ana; Pérez Sinusía, Ester; Biel Ibáñez, María Pilar; Fernández Vázquez, Aranzazu; Hernández Giménez, Mónica. Aplicación de un sistema de Erúbricas para la evaluación de los trabajos de módulo en el Grado en Ingeniería en Diseño Industrial y Desarrollo de Producto. REDU. REVISTA DE DOCENCIA UNIVERSITARIA. 2014
  
  
• Serrano Tierz, Ana; Hernández Giménez, Mónica; Pérez Sinusía, Ester ; Biel Ibáñez, Pilar. Trabajo por módulos: un modelo de aprendizaje interdisciplinar y colaborativo en el Grado en Ingeniería en Diseño Industrial y Desarrollo de Producto. REDU. REVISTA DE DOCENCIA UNIVERSITARIA. 2013. DOI: 10.4995/redu.2013.5553
  
  
• Hernandez, M.;Bossa,M. N.;Olmos,S. Registration of Anatomical Images using Paths of Diffeomorphisms Parameterized with Stationary Vector Field Flows. INTERNATIONAL JOURNAL OF COMPUTER VISION. 2009
  
  
• Hernandez, M.;Olmos,S. Gauss-Newton Optimization in Diffeomorphic Registration. PROCEEDINGS - INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING. 2008
  
  
• Bossa, M.;Hernandez,M.;Olmos,S. Contributions to 3D Diffeomorphic Atlas Estimation: Application to Brain Images. LECTURE NOTES IN COMPUTER SCIENCE. 2007
  
  
• Hernandez, M.;Bossa,M. N.;Olmos,S. Registration of Anatomical Images using Geodesic Paths of Diffeomorphisms Parameterized with Stationary Vector Fields. PROCEEDINGS (IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION). 2007
  
  
• Hernandez, M.;Frangi,A. F. Non-Parametric Geodesic Active Regions: Method and Evaluation for Cerebral Aneurysms Segmentation in 3DRA and CTA. MEDICAL IMAGE ANALYSIS. 2007
  
  
• Hernandez, M.;Frangi, A. F.;Sapiro, G. Three-Dimensional Segmentation of Brain Aneurysms in Cta Using Non-Parametric Region-Based Information and Implicit Deformable Models: Method and Evaluation. LECTURE NOTES IN COMPUTER SCIENCE. 2003
  
  

Conference presentations

• Ramón Júlvez, Ubaldo; Hernández Giménez, Mónica; Mayordomo Cámara, Elvira;. LDDMM meets GANs: generative adversarial networks for diffeomorphic registration. LECTURE NOTES IN COMPUTER SCIENCE. 2022. DOI: 10.1007/978-3-031-11203-4_3
  
  
• Marin, Belen; Alquezar-Baeta, Carlos; Hernandez, Monica; Mayordomo Cámara, Elvira. Evolution of GWAS results through ADNI cohorts. PROCEEDINGS (IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE). 2018. DOI: 10.1109/BIBM.2018.8621358
  
  
• Hernández,M.;Artacho,J. M.;Mellado,X.;Cruz,S. Smooth intensity maps for IMRT. PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING. 2011. DOI: 10.1109/ICASSP.2011.5946508
  
  

Projects

• PID2022-138703OB-I00: Inteligencia artificial explicable hacia soluciones de diagnóstico asistido por computador usables y fiables para enfermedades neurodegenerativas: tendiendo puentes de conocimiento entre el cerebro y el ojo a través del nervio óptico (Trust-BEyE). 01/09/23 - 31/08/26
  
  
• PID2019-104358RB-I00: Métodos para el diagnóstico y pronóstico asistidos por computador de enfermedades neurodegenerativas mediante anatomía computacional, genética en imagen y deep-learning. 01/06/20 - 29/02/24
  
  
• TIN2016-80347-R: INTEGRACIÓN DE MODELOS BIOINFORMÁTICOS, COGNITIVOS Y DE ANATOMÍA COMPUTACIONAL PARA LA MEJORA DEL DIAGNÓSTICO DE ENFERMEDADES NEURODEGENERATIVAS. 30/12/16 - 31/12/20
  
  

Supervision of final year projects

• MODELOS DE FORMA 3D PARA SEGMENTACIÓN DE IMÁGENES MÉDICAS. Universidad de Zaragoza. Sobresaliente. 16/03/06
  
  
• APLICACION DE METODOS DE EVOLUCION DE SUPERFICIES Y LEVEL-SETS A LA SEGMENTACION DE IMAGENES MEDICAS TRIDIMENSIONALES. Universidad de Zaragoza. Sobresaliente. 10/07/02
  
  

Supervision of undergraduate dissertations

• Estudio de modelos de reducción de una dimensionalidad en registro difeomorfo bajo la ecuación de Euler-Poincaré. Universidad de Zaragoza. Matrícula de honor. 23/09/24
  
  
• Modelos de supervivencia e inteligencia artificial explicable en la predicción del riesgo de conversión de deterioro cognitivo leve a Alzhéimer. Universidad de Zaragoza. Sobresaliente. 16/07/24
  
  
• Morfometría basada en tensores mediante métodos de registro de imágenes médicas basados en aprendizaje profundo. Universidad de Zaragoza. Matrícula de honor. 02/02/24
  
  
• Análisis de VoxelMorph en diferentes entornos de desarrollo: Tensor flow vs PyTorch vs Matlab. Universidad de Zaragoza. Sobresaliente. 22/06/23
  
  
• Un modelo predictivo basado en deep learning para la caracterización de la evolución de la enfermedad de Alzheimer. Universidad de Zaragoza. Sobresaliente. 10/09/19
  
  

Supervision of master's theses

• Registro multi-modal de imágenes médicas mediante aprendizaje profundo. Universidad de Zaragoza. Matrícula de honor. 21/12/23
  
  
• Descomposición Ortogonal Propia en registro mediante difeomorfismos. Universidad de Zaragoza. Sobresaliente. 22/09/22
  
  
• LDDMM y GANs: Redes Generativas Antagónicas para registro difeomorfico. Universidad de Zaragoza. Matrícula de honor. 11/02/22
  
  

UNIZAR teaching of the last six courses

• Fundamentals of computer studies. Bachelor's Degree in Electronic and Automatic Engineering. During academic year 2024-25
  
  
• Agile methodologies and quality. From the 2022-23 course to the 2024-25 course
  
  
• Computer vision. From the 2022-23 course to the 2024-25 course
  
  
• Computer science theory. From the 2021-22 course to the 2024-25 course
  
  
• Computer vision. Bachelor's Degree in Informatics Engineering. From the 2020-21 course to the 2024-25 course
  
  
• Agile methodologies and quality. Bachelor's Degree in Informatics Engineering. From the 2019-20 course to the 2024-25 course
  
  
• Computer science theory. Bachelor's Degree in Informatics Engineering. From the 2019-20 course to the 2024-25 course
  
  
• Algorithms for difficult problems. Bachelor's Degree in Informatics Engineering. During academic year 2023-24
  
  
• Algorithms for difficult problems. During academic year 2023-24
  
  
• Internships 6. Bachelor's Degree in Informatics Engineering. During academic year 2023-24
  
  
• Undergraduate dissertation. Bachelor's Degree in Informatics Engineering. During academic year 2023-24
  
  
• Undergraduate dissertation. During academic year 2023-24
  
  
• Undergraduate dissertation. Bachelor's Degree in Informatics Engineering. During academic year 2023-24
  
  
• Undergraduate dissertation. Bachelor's Degree in Informatics Engineering. During academic year 2023-24
  
  
• Databases. Bachelor's Degree in Informatics Engineering. From the 2019-20 course to the 2023-24 course
  
  
• Fundamentals of computer studies. Bachelor's Degree in Electronic and Automatic Engineering. From the 2019-20 course to the 2020-21 course