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Jorge Novo
Jorge Novo Buján
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2020 – today
- 2024
- [j62]Lorena Álvarez-Rodríguez
, Ana Pueyo, Joaquim de Moura
Fully automatic deep convolutional approaches for the screening of neurodegeneratives diseases using multi-view OCT images. Artif. Intell. Medicine 158: 103006 (2024) - [j61]Emilio López-Varela
Evolutionary multi-target neural network architectures for flow void analysis in optical coherence tomography angiography. Appl. Soft Comput. 153: 111304 (2024) - [j60]Elena Goyanes
Automatic simultaneous ciliary muscle segmentation and biomarker extraction in AS-OCT images using deep learning-based approaches. Biomed. Signal Process. Control. 90: 105851 (2024) - [j59]Mateo Gende, Joaquim de Moura
Circumpapillary OCT-based multi-sector analysis of retinal layer thickness in patients with glaucoma and high myopia. Comput. Medical Imaging Graph. 118: 102464 (2024) - [j58]Álvaro S. Hervella
Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity. Medical Biol. Eng. Comput. 62(3): 865-881 (2024) - [j57]Daniel Iglesias Morís
Adapted generative latent diffusion models for accurate pathological analysis in chest X-ray images. Medical Biol. Eng. Comput. 62(7): 2189-2212 (2024) - [j56]David Rivas-Villar, Álvaro S. Hervella, José Rouco, Jorge Novo:
ConKeD: multiview contrastive descriptor learning for keypoint-based retinal image registration. Medical Biol. Eng. Comput. 62(12): 3721-3736 (2024) - [j55]Álvaro S. Hervella
Multi-Adaptive Optimization for multi-task learning with deep neural networks. Neural Networks 170: 254-265 (2024) - [c80]Álvaro S. Hervella, José Rouco, Jorge Novo, Clara I. Sánchez, Marcos Ortega:
Recurrent Task Specialization Network for Segmentation-aided Vascular Landmarks Detection in Retinal Images. ECAI 2024: 688-695 - [i9]David Rivas-Villar, Álvaro S. Hervella, José Rouco, Jorge Novo:
ConKeD: Multiview contrastive descriptor learning for keypoint-based retinal image registration. CoRR abs/2401.05901 (2024) - [i8]David Rivas-Villar, Álvaro S. Hervella, José Rouco, Jorge Novo:
ConKeD++ - Improving descriptor learning for retinal image registration: A comprehensive study of contrastive losses. CoRR abs/2404.16773 (2024) - 2023
- [j54]Plácido L. Vidal, Joaquim de Moura
Comprehensive fully-automatic multi-depth grading of the clinical types of macular neovascularization in OCTA images. Appl. Intell. 53(21): 25897-25918 (2023) - [j53]Plácido L. Vidal
Image-to-image translation with Generative Adversarial Networks via retinal masks for realistic Optical Coherence Tomography imaging of Diabetic Macular Edema disorders. Biomed. Signal Process. Control. 79(Part): 104098 (2023) - [j52]Daniel Iglesias Morís
Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models. Biomed. Signal Process. Control. 84: 104818 (2023) - [j51]Daniel Iglesias Morís
Context encoder transfer learning approaches for retinal image analysis. Comput. Biol. Medicine 152: 106451 (2023) - [j50]Emilio López-Varela
Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images. Comput. Medical Imaging Graph. 104: 102172 (2023) - [j49]José Morano
Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning. Comput. Methods Programs Biomed. 229: 107296 (2023) - [j48]Mateo Gende
A new generative approach for optical coherence tomography data scarcity: unpaired mutual conversion between scanning presets. Medical Biol. Eng. Comput. 61(5): 1093-1112 (2023) - [j47]Plácido L. Vidal, Joaquim de Moura
Multivendor fully automatic uncertainty management approaches for the intuitive representation of DME fluid accumulations in OCT images. Medical Biol. Eng. Comput. 61(5): 1209-1224 (2023) - [j46]Javier Martínez-Río, Enrique J. Carmona
Deformable registration of multimodal retinal images using a weakly supervised deep learning approach. Neural Comput. Appl. 35(20): 14779-14797 (2023) - [j45]Mateo Gende
Automatic Segmentation of Retinal Layers in Multiple Neurodegenerative Disorder Scenarios. IEEE J. Biomed. Health Informatics 27(11): 5483-5494 (2023) - [c79]Plácido L. Vidal, Joaquim de Moura
Transformer-Based Multi-Prototype Approach for Diabetic Macular Edema Analysis in OCT Images. ICASSP 2023: 1-5 - [c78]Daniel Iglesias Morís
Deep feature analysis in a transfer learning approach for the automatic COVID-19 screening using chest X-ray images. KES 2023: 228-237 - [c77]Daniel Olañeta, Daniel Iglesias Morís
Explainable learning to analyze the outcome of COVID-19 patients using clinical data. KES 2023: 238-247 - 2022
- [j44]Joaquim de Moura
Fully automatic deep convolutional approaches for the analysis of COVID-19 using chest X-ray images. Appl. Soft Comput. 115: 108190 (2022) - [j43]Álvaro S. Hervella
End-to-end multi-task learning for simultaneous optic disc and cup segmentation and glaucoma classification in eye fundus images. Appl. Soft Comput. 116: 108347 (2022) - [j42]David Rivas-Villar
Color fundus image registration using a learning-based domain-specific landmark detection methodology. Comput. Biol. Medicine 140: 105101 (2022) - [j41]Álvaro S. Hervella, José Rouco, Jorge Novo
Multimodal image encoding pre-training for diabetic retinopathy grading. Comput. Biol. Medicine 143: 105302 (2022) - [j40]Mateo Gende
End-to-end multi-task learning approaches for the joint epiretinal membrane segmentation and screening in OCT images. Comput. Medical Imaging Graph. 98: 102068 (2022) - [j39]Álvaro S. Hervella
Retinal microaneurysms detection using adversarial pre-training with unlabeled multimodal images. Inf. Fusion 79: 146-161 (2022) - [j38]Emilio López-Varela
Fully-Automatic 3D Intuitive Visualization of Age-Related Macular Degeneration Fluid Accumulations in OCT Cubes. J. Digit. Imaging 35(5): 1271-1282 (2022) - [j37]Joaquim de Moura
Feature definition and comprehensive analysis on the robust identification of intraretinal cystoid regions using optical coherence tomography images. Pattern Anal. Appl. 25(1): 1-15 (2022) - [j36]Daniel Iglesias Morís
Unsupervised contrastive unpaired image generation approach for improving tuberculosis screening using chest X-ray images. Pattern Recognit. Lett. 164: 60-66 (2022) - [c76]Mateo Gende
Impact of the Region of Analysis on the Performance of the Automatic Epiretinal Membrane Segmentation in OCT Images. EUROCAST 2022: 395-402 - [c75]Daniel Iglesias Morís
Performance Analysis of GAN Approaches in the Portable Chest X-Ray Synthetic Image Generation for COVID-19 Screening. EUROCAST 2022: 403-410 - [c74]Iván Barrientos
Clinical Decision Support Tool for the Identification of Pathological Structures Associated with Age-Related Macular Degeneration. EUROCAST 2022: 411-418 - [c73]David Rivas-Villar
Deep Features-Based Approaches for Phytoplankton Classification in Microscopy Images. EUROCAST 2022: 419-426 - [c72]Alejandro Budiño
Robust Deep Learning-Based Approach for Retinal Layer Segmentation in Optical Coherence Tomography Images. EUROCAST 2022: 427-434 - [c71]José Morano
Impact of Increased Centerline Weight on the Joint Segmentation and Classification of Arteries and Veins in Color Fundus Images. EUROCAST 2022: 435-443 - [c70]Plácido L. Vidal
Pulmonary-Restricted COVID-19 Informative Visual Screening Using Chest X-ray Images from Portable Devices. ICIAP (1) 2022: 65-76 - [c69]Emilio López-Varela
Unsupervised Deformable Image Registration in a Landmark Scarcity Scenario: Choroid OCTA. ICIAP (1) 2022: 89-99 - [c68]José Morano
Improving AMD Diagnosis by the Simultaneous Identification of Associated Retinal Lesions. ICIAP (1) 2022: 148-159 - [c67]Mateo Gende
High/Low Quality Style Transfer for Mutual Conversion of OCT Images Using Contrastive Unpaired Translation Generative Adversarial Networks. ICIAP (1) 2022: 210-220 - [c66]Elena Goyanes
Fully-automatic segmentation of the ciliary muscle using anterior segment optical coherence tomography images. IJCNN 2022: 1-8 - [c65]José Morano, Álvaro S. Hervella, Jorge Novo, José Rouco:
Web-based platform for the automatic analysis and visualization of vascular diagnostic markers in ophthalmological images. XoveTIC 2022: 60-62 - [c64]Mateo Gende, Joaquim de Moura
Multi-task Convolutional Neural Networks for the End-to-end Simultaneous Segmentation and Screening of the Epiretinal Membrane in OCT Images. XoveTIC 2022: 77-79 - [c63]Daniel Iglesias Morís
Portable chest X-ray image generation for the improvement of the automatic COVID-19 screening. XoveTIC 2022: 104-107 - [c62]Plácido Francisco Lizancos Vidal, Joaquim de Moura
Region of interest-bounded COVID-19 lung screening using images from portable X-ray devices. XoveTIC 2022: 111-114 - [c61]David Rivas-Villar, Álvaro S. Hervella, José Rouco, Jorge Novo:
Deep learning-based detection of domain-specific retinal landmarks for color fundus image registration. XoveTIC 2022: 127-129 - [c60]Lorena Álvarez
Analysis of Imbalanced Datasets in the Performance of Deep Learning Approaches for COVID-19 Screening from Chest X-ray Imaging: Impact of Sex and Age Factors. XoveTIC 2022: 174-177 - [i7]José Morano, Álvaro S. Hervella, José Rouco, Jorge Novo, José Ignacio Fernández-Vigo
Improving AMD diagnosis by the simultaneous identification of associated retinal lesions. CoRR abs/2205.10885 (2022) - [i6]José Morano, Álvaro S. Hervella, Jorge Novo, José Rouco:
Simultaneous segmentation and classification of the retinal arteries and veins from color fundus images. CoRR abs/2209.09582 (2022) - [i5]José Morano, Álvaro S. Hervella, José Rouco, Jorge Novo, José Ignacio Fernández-Vigo, Marcos Ortega:
Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning. CoRR abs/2212.00565 (2022) - 2021
- [j35]Mateo Gende
Automatic Segmentation and Intuitive Visualisation of the Epiretinal Membrane in 3D OCT Images Using Deep Convolutional Approaches. IEEE Access 9: 75993-76004 (2021) - [j34]José Morano
Simultaneous segmentation and classification of the retinal arteries and veins from color fundus images. Artif. Intell. Medicine 118: 102116 (2021) - [j33]Javier Martínez-Río
Robust multimodal registration of fluorescein angiography and optical coherence tomography angiography images using evolutionary algorithms. Comput. Biol. Medicine 134: 104529 (2021) - [j32]David Rivas-Villar, José Rouco
Fully automatic detection and classification of phytoplankton specimens in digital microscopy images. Comput. Methods Programs Biomed. 200: 105923 (2021) - [j31]Plácido L. Vidal
Multi-stage transfer learning for lung segmentation using portable X-ray devices for patients with COVID-19. Expert Syst. Appl. 173: 114677 (2021) - [j30]Álvaro S. Hervella
Self-supervised multimodal reconstruction pre-training for retinal computer-aided diagnosis. Expert Syst. Appl. 185: 115598 (2021) - [j29]Daniel Iglesias Morís
Data augmentation approaches using cycle-consistent adversarial networks for improving COVID-19 screening in portable chest X-ray images. Expert Syst. Appl. 185: 115681 (2021) - [c59]Joaquim de Moura
Automated Segmentation of the Central Serous Chorioretinopathy fluid regions using Optical Coherence Tomography Scans. CBMS 2021: 1-6 - [c58]Macarena Díaz, Plácido L. Vidal
Automatic Segmentation and Estimation of Ischemic Regions in Oct Angiography Scans. CBMS 2021: 7-12 - [c57]Plácido L. Vidal
Comparative and Behavioural Analysis of a Diffuse Paradigm for the Evaluation of Diabetic Macular Edema in OCT images. CBMS 2021: 13-18 - [c56]Daniel Iglesias Morís, Joaquim de Moura, Jorge Novo, Marcos Ortega:
Comprehensive Analysis of the Screening of COVID-19 Approaches in Chest X-ray Images from Portable Devices. ESANN 2021 - [c55]Daniel Iglesias Morís
Cycle Generative Adversarial Network Approaches to Produce Novel Portable Chest X-Rays Images for Covid-19 Diagnosis. ICASSP 2021: 1060-1064 - [c54]Daniel Iglesias Morís
Context encoder self-supervised approaches for eye fundus analysis. IJCNN 2021: 1-8 - 2020
- [j28]Enrique J. Carmona
Modeling, Localization, and Segmentation of the Foveal Avascular Zone on Retinal OCT-Angiography Images. IEEE Access 8: 152223-152238 (2020) - [j27]Joaquim de Moura
Deep Convolutional Approaches for the Analysis of COVID-19 Using Chest X-Ray Images From Portable Devices. IEEE Access 8: 195594-195607 (2020) - [j26]Álvaro S. Hervella
Learning the retinal anatomy from scarce annotated data using self-supervised multimodal reconstruction. Appl. Soft Comput. 91: 106210 (2020) - [j25]Álvaro S. Hervella
Deep multi-instance heatmap regression for the detection of retinal vessel crossings and bifurcations in eye fundus images. Comput. Methods Programs Biomed. 186: 105201 (2020) - [j24]Álvaro S. Hervella
Self-supervised multimodal reconstruction of retinal images over paired datasets. Expert Syst. Appl. 161: 113674 (2020) - [j23]Joaquim de Moura
Joint Diabetic Macular Edema Segmentation and Characterization in OCT Images. J. Digit. Imaging 33(5): 1335-1351 (2020) - [j22]Joaquim de Moura
Intraretinal Fluid Pattern Characterization in Optical Coherence Tomography Images. Sensors 20(7): 2004 (2020) - [j21]David Rivas-Villar
Automatic Detection of Freshwater Phytoplankton Specimens in Conventional Microscopy Images. Sensors 20(22): 6704 (2020) - [c53]José Morano
Multimodal Transfer Learning-Based Approaches for Retinal Vascular Segmentation. ECAI 2020: 1866-1873 - [c52]Álvaro S. Hervella
Multi-Modal Self-Supervised Pre-Training for Joint Optic Disc and Cup Segmentation in Eye Fundus Images. ICASSP 2020: 961-965 - [i4]Plácido L. Vidal, Joaquim de Moura
Multi-stage transfer learning for lung segmentation using portable X-ray devices for patients with COVID-19. CoRR abs/2011.00133 (2020) - [i3]José Morano
Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation. CoRR abs/2012.10160 (2020)
2010 – 2019
- 2019
- [j20]Víctor Manuel Mondéjar-Guerra
Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers. Biomed. Signal Process. Control. 47: 41-48 (2019) - [j19]Alba Fernández, Marcos Ortega
Automatic evaluation of eye gestural reactions to sound in video sequences. Eng. Appl. Artif. Intell. 85: 164-174 (2019) - [j18]Joaquim de Moura
Artery/Vein Vessel Tree Identification in Near-Infrared Reflectance Retinographies. J. Digit. Imaging 32(6): 947-962 (2019) - [j17]Macarena Díaz
Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies. Sensors 19(21): 4732 (2019) - [j16]Pablo Cabaleiro, Joaquim de Moura
Automatic Identification and Representation of the Cornea-Contact Lens Relationship Using AS-OCT Images. Sensors 19(23): 5087 (2019) - [j15]Sergio Baamonde
Automatic Identification and Intuitive Map Representation of the Epiretinal Membrane Presence in 3D OCT Volumes. Sensors 19(23): 5269 (2019) - [c51]Víctor Manuel Mondéjar-Guerra, José Rouco, Jorge Novo, Marcos Ortega:
An end-to-end deep learning approach for simultaneous background modeling and subtraction. BMVC 2019: 266 - [c50]Iago Otero Coto, Plácido Francisco Lizancos Vidal, Joaquim de Moura, Jorge Novo, Marcos Ortega:
Computerized tool for identification and enhanced visualization of Macular Edema regions using OCT scans. ESANN 2019 - [c49]Álvaro S. Hervella
Impact of the Circular Region of Interest on the Performance of Multimodal Reconstruction of Retinal Images. EUROCAST (2) 2019: 222-230 - [c48]Joaquim de Moura
Automatic Identification of Diabetic Macular Edema Biomarkers Using Optical Coherence Tomography Scans. EUROCAST (2) 2019: 247-255 - [c47]Plácido L. Vidal
Intuitive and Coherent Intraretinal Cystoid Map Representation in Optical Coherence Tomography Images. EUROCAST (2) 2019: 270-278 - [c46]Víctor Manuel Mondéjar-Guerra
Automatic ECG Screening as a Supporting Tool on a Telemedicine Framework. EUROCAST (2) 2019: 289-296 - [c45]Álvaro S. Hervella
Self-Supervised Deep Learning for Retinal Vessel Segmentation Using Automatically Generated Labels from Multimodal Data. IJCNN 2019: 1-8 - [c44]Álvaro S. Hervella
Deep Multimodal Reconstruction of Retinal Images Using Paired or Unpaired Data. IJCNN 2019: 1-8 - [c43]Joaquim de Moura
Deep Feature Analysis in a Transfer Learning-based Approach for the Automatic Identification of Diabetic Macular Edema. IJCNN 2019: 1-8 - [c42]Plácido L. Vidal
Cystoid Fluid Color Map Generation in Optical Coherence Tomography Images Using a Densely Connected Convolutional Neural Network. IJCNN 2019: 1-8 - [c41]Macarena Díaz, Joaquim de Moura
Automatic wide field registration and mosaicking of OCTA images using vascularity information. KES 2019: 505-513 - [c40]Joaquim de Moura
Retinal vascular analysis in a fully automated method for the segmentation of DRT edemas using OCT images. KES 2019: 600-609 - [c39]Sergio Baamonde, Martiño Cabana
Fully automatic multi-temporal land cover classification using Sentinel-2 image data. KES 2019: 650-657 - 2018
- [j14]Gabriela Samagaio, Aída Estévez, Joaquim de Moura
Automatic macular edema identification and characterization using OCT images. Comput. Methods Programs Biomed. 163: 47-63 (2018) - [j13]Alba Fernández, Marcos Ortega
Detection of reactions to sound via gaze and global eye motion analysis using camera streaming. Mach. Vis. Appl. 29(7): 1069-1082 (2018) - [c38]Álvaro S. Hervella
Multimodal registration of retinal images using domain-specific landmarks and vessel enhancement. KES 2018: 97-104 - [c37]Joaquim de Moura
Automatic Characterization of the Serous Retinal Detachment Associated with the Subretinal Fluid Presence in Optical Coherence Tomography Images. KES 2018: 244-253 - [c36]Macarena Díaz, Jorge Novo
Automatic extraction of vascularity measurements using OCT-A images. KES 2018: 273-281 - [c35]Gabriela Samagaio, Joaquim de Moura
Automatic Segmentation of Diffuse Retinal Thickening Edemas Using Optical Coherence Tomography Images. KES 2018: 472-481 - [c34]Lucía Ramos
Multi-expert analysis and validation of objective vascular tortuosity measurements. KES 2018: 482-489 - [c33]Álvaro S. Hervella
Retinal Image Understanding Emerges from Self-Supervised Multimodal Reconstruction. MICCAI (1) 2018: 321-328 - [c32]Gabriela Samagaio, Aída Estévez, Joaquim de Moura
Automatic Identification of Macular Edema in Optical Coherence Tomography Images. VISIGRAPP (4: VISAPP) 2018: 533-540 - [i2]Álvaro S. Hervella, José Rouco, Jorge Novo, Marcos Ortega:
Multimodal Registration of Retinal Images Using Domain-Specific Landmarks and Vessel Enhancement. CoRR abs/1803.00951 (2018) - [i1]Macarena Díaz, Jorge Novo, Paula Cutrín, Francisco Gómez-Ulla, Manuel G. Penedo, Marcos Ortega:
Automatic segmentation of the Foveal Avascular Zone in ophthalmological OCT-A images. CoRR abs/1811.10374 (2018) - 2017
- [j12]Jorge Novo
Hydra: A web-based system for cardiovascular analysis, diagnosis and treatment. Comput. Methods Programs Biomed. 139: 61-81 (2017) - [j11]Joaquim de Moura
Enhanced visualization of the retinal vasculature using depth information in OCT. Medical Biol. Eng. Comput. 55(12): 2209-2225 (2017) - [c31]Joaquim de Moura
Automatic Identification of Intraretinal Cystoid Regions in Optical Coherence Tomography. AIME 2017: 305-315 - [c30]Joaquim de Moura
Interactive Three-Dimensional Visualization System of the Vascular Structure in OCT Retinal Images. EUROCAST (2) 2017: 306-313 - [c29]Joaquim de Moura
Automatic Retinal Vascularity Identification and Artery/Vein Classification Using Near-Infrared Reflectance Retinographies. VISIGRAPP (Revised Selected Papers) 2017: 262-278 - [c28]Gabriela Samagaio, Joaquim de Moura
Optical Coherence Tomography Denoising by Means of a Fourier Butterworth Filter-Based Approach. ICIAP (2) 2017: 422-432 - [c27]Sergio Baamonde
Feature Definition and Selection for Epiretinal Membrane Characterization in Optical Coherence Tomography Images. ICIAP (2) 2017: 456-466 - [c26]Sergio Baamonde
Automatic Detection of Epiretinal Membrane in OCT Images by Means of Local Luminosity Patterns. IWANN (1) 2017: 222-235 - [c25]Joaquim de Moura
Automatic Detection of Blood Vessels in Retinal OCT Images. IWINAC (2) 2017: 3-10 - [c24]Joaquim de Moura
Automatic vessel detection by means of brightness profile characterization in OCT images. KES 2017: 980-988 - [c23]Joaquim de Moura
Feature definition, analysis and selection for cystoid region characterization in Optical Coherence Tomography. KES 2017: 1369-1377 - [c22]Luis Gonçalves, Jorge Novo, António Cunha
Evaluation of the Degree of Malignancy of Lung Nodules in Computed Tomography Images. VISIGRAPP (6: VISAPP) 2017: 74-80 - [c21]Joaquim de Moura
Artery/vein Classification of Blood Vessel Tree in Retinal Imaging. VISIGRAPP (4: VISAPP) 2017: 371-377 - 2016
- [j10]Luis Gonçalves, Jorge Novo Buján
Hessian based approaches for 3D lung nodule segmentation. Expert Syst. Appl. 61: 1-15 (2016) - [c20]Joaquim de Moura
Vessel Tree Extraction and Depth Estimation with OCT Images. CAEPIA 2016: 23-33 - [c19]Luis Gonçalves, Jorge Novo, Aurélio Campilho:
Feature definition, analysis and selection for lung nodule classification in chest computerized tomography images. ESANN 2016 - [c18]Luis Gonçalves, Jorge Novo
Central Medialness Adaptive Strategy for 3D Lung Nodule Segmentation in Thoracic CT Images. ICIAR 2016: 583-590 - [c17]Joaquim de Moura
3D Retinal Vessel Tree Segmentation and Reconstruction with OCT Images. ICIAR 2016: 716-726 - 2015
- [c16]Jorge Novo
3D lung nodule candidate detection in multiple scales. MVA 2015: 61-64 - 2014
- [c15]José Rouco
On the Automatic Normalization of Plaque Regions in Ultrasound Images of the Carotid. ICIAR (2) 2014: 177-184 - [c14]Jorge Novo
Reliable Lung Segmentation Methodology by Including Juxtapleural Nodules. ICIAR (2) 2014: 227-235 - 2013
- [j9]Jorge Novo
Multiobjective differential evolution in the optimization of topological active models. Appl. Soft Comput. 13(6): 3167-3177 (2013) - [j8]Beatriz Remeseiro
Automatic classification of the interferential tear film lipid layer using colour texture analysis. Comput. Methods Programs Biomed. 111(1): 93-103 (2013) - [j7]Brais Cancela
On the use of a minimal path approach for target trajectory analysis. Pattern Recognit. 46(7): 2015-2027 (2013) - [c13]Luisa Sánchez
Unified methodology for evaluating vessel tree tortuosity metrics in eye fundus images. CBMS 2013: 528-529 - [c12]Ana González, Manuel G. Penedo, Sonia González-Vázquez
Cost Function Selection for a Graph-Based Segmentation in OCT Retinal Images. EUROCAST (2) 2013: 125-132 - [c11]Cristina V. Sierra, Jorge Novo, José Santos Reyes, Manuel G. Penedo:
Emergent Segmentation of Topological Active Nets by Means of Evolutionary Obtained Artificial Neural Networks. ICAART (2) 2013: 44-50 - [c10]Jorge Novo
Emergent Image Segmentation by Means of Evolved Connectionist Models and Using a Topological Active Net Model. ICAART (Revised Selected Papers) 2013: 149-161 - 2012
- [j6]Beatriz Remeseiro
Statistical Comparison of Classifiers Applied to the Interferential Tear Film Lipid Layer Automatic Classification. Comput. Math. Methods Medicine 2012: 207315:1-207315:10 (2012) - [j5]Jorge Novo
Topological Active Models optimization with Differential Evolution. Expert Syst. Appl. 39(15): 12165-12176 (2012) - [j4]Jorge Novo
Topological Active Volume 3D segmentation model optimized with genetic approaches. Nat. Comput. 11(1): 161-174 (2012) - [c9]Cristina V. Sierra, Jorge Novo, José Santos Reyes, Manuel G. Penedo:
Evolved artificial neural networks for controlling Topological Active Nets deformation and for medical image segmentation. KES 2012: 1380-1389 - 2011
- [c8]Jorge Novo, Manuel G. Penedo, José Santos Reyes:
Multiobjective Optimization of the 3D Topological Active Volume Segmentation Model. ICAART (1) 2011: 236-241 - [c7]Jorge Novo Buján, José Santos Reyes, Manuel G. Penedo
Optimization of Topological Active Nets with Differential Evolution. ICANNGA (1) 2011: 350-360 - [c6]Jorge Novo
Differential Evolution Optimization of 3D Topological Active Volumes. IWANN (1) 2011: 282-290 - 2010
- [j3]Marcos Ortega
Sirius: A web-based system for retinal image analysis. Int. J. Medical Informatics 79(10): 722-732 (2010) - [j2]Jorge Novo
Evolutionary multiobjective optimization of Topological Active Nets. Pattern Recognit. Lett. 31(13): 1781-1794 (2010) - [c5]Lucía Ramos
Color Video Segmentation by Dissimilarity Based on Edges. HAIS (2) 2010: 264-271 - [c4]Jorge Novo
Optimization of Topological Active Models with Multiobjective Evolutionary Algorithms. ICPR 2010: 2226-2229
2000 – 2009
- 2009
- [j1]Jorge Novo
Localisation of the optic disc by means of GA-optimised Topological Active Nets. Image Vis. Comput. 27(10): 1572-1584 (2009) - [c3]Marcos Ortega
Vascular Landmark Detection in Retinal Images. EUROCAST 2009: 211-217 - [c2]Jorge Novo
Genetic Approaches for the Automatic Division of Topological Active Volumes. IWINAC (2) 2009: 20-29 - 2008
- [c1]Jorge Novo
Optic Disc Segmentation by Means of GA-Optimized Topological Active Nets. ICIAR 2008: 807-816
Coauthor Index
Joaquim de Moura
aka: José Joaquim de Moura Ramos
aka: José Joaquim de Moura Ramos
[j62] [j61] [j60] [j59] [j57] [j54] [j53] [j52] [j50] [j48] [j47] [j45] [c79] [c78] [c77] [j44] [j40] [j37] [j36] [c76] [c75] [c74] [c72] [c70] [c67] [c66] [c64] [c63] [c62] [c60] [j35] [j31] [j29] [c59] [c57] [c56] [c55] [j27] [j23] [j22] [i4] [j19] [j18] [j16] [j15] [c50] [c48] [c47] [c43] [c42] [c41] [c40] [j14] [j13] [c37] [c35] [c32] [j11] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c21] [c20] [c17]
Marcos Ortega
aka: Marcos Ortega Hortas
aka: Marcos Ortega Hortas
[j62] [j61] [j60] [j59] [j58] [j57] [j55] [c80] [j54] [j53] [j52] [j51] [j50] [j49] [j48] [j47] [j46] [j45] [c79] [c78] [c77] [j44] [j43] [j41] [j40] [j39] [j38] [j37] [j36] [c76] [c75] [c74] [c72] [c70] [c69] [c68] [c67] [c66] [c64] [c63] [c62] [c60] [i7] [i5] [j35] [j33] [j31] [j30] [j29] [c59] [c58] [c57] [c56] [c55] [c54] [j28] [j27] [j26] [j25] [j24] [j23] [j22] [c52] [i4] [j20] [j19] [j18] [j17] [j16] [j15] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [j14] [j13] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [i2] [i1] [j12] [j11] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c21] [c20] [c17] [j7] [j3] [c3]
Manuel G. Penedo
aka: Manuel Francisco González Penedo
aka: Manuel Francisco González Penedo
[j58] [j56] [j55] [c80] [i9] [i8] [j51] [j49] [j43] [j42] [j41] [j39] [j37] [c73] [c71] [c68] [c65] [c61] [i7] [i6] [i5] [j34] [j32] [j30] [c54] [j26] [j25] [j24] [j22] [j21] [c53] [c52] [i3] [j20] [j18] [c51] [c49] [c46] [c45] [c44] [c38] [c34] [c33] [i2] [c31] [c27] [c25] [c24] [c23] [c15] [c14] [c5] [c3]
Plácido L. Vidal
aka: Plácido Francisco Lizancos Vidal
aka: Plácido Francisco Lizancos Vidal
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