Publications

Lina Ruiz, Franklin Sierra-Jerez, Jair Ruiz, Fabio Martinez. COLON: The largest COlonoscopy LONg sequence public database.2024. arXiv:2403.00663

Moreno A, Bautista LX, Martínez F. Cardiac disease discrimination from 3d-convolutional kinematic patterns on cine-MRI sequences. Biomédica. 2024;44 

Sierra Franklin  and Martínez, F. (2024). A non-aligned translation with a neoplastic classifier regularization to include vascular NBI patterns in standard colonoscopies. Accepted in Journal of Computer in Biology and Medicine. Elsevier. 

Sebastian Florez, Santiago Gómez, Julian Garcia, and Fabio Martínez   and Martínez, F. (2024). A deep cascade architecture that generates synthetic parametric maps and segment stroke lesions over CT studies. IV LAWCN - Latin American Workshop on comptuational neuroscience

Jean Portilla, Edgar rangel  and Martínez, F. (2023). A volumetric deep architecture to discriminate parkinsonian patterns from intermediate pose representations. IV LAWCN- Latin American Workshop on comptuational neuroscience

Valenzuela, B., Viáfara, C. C., Penagos, J. J., & Martínez, F. (2023). Wear mechanisms and severity level classification in iron ore transfer chute linings by propagating regional labels coded as embedding deep learning vectors. Materials Today Communications, 107952.

Gómez, S., Mantilla, D., Valenzuela, B., Ortiz, A., D Vera, D., Camacho, P., & Martínez, F. (2023, October). Ischemic Stroke Segmentation from a Cross-Domain Representation in Multimodal Diffusion Studies. In MICCAI - International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 776-785)

Romero, W. D., Torres-Bermudez, S., Valenzuela, B., Viáfara, C. C., Meléndez, A. M., & Martínez, F. (2023). Geometrical recognition of metallic foam microstructures using a deep learning approach. Materials Today Communications, 107407.

Juan Olmos, Antoine Manzanera, Fabio Martínez. Riemannian SPD learning to represent and characterize fixational oculomotor Parkinsonian abnormalities. Pattern Recognition Letters. 2023. https://doi.org/10.1016/j.patrec.2023.09.012

• Olmos, J., Valenzuela, B. & Martínez, F. Quantification of Parkinsonian unilateral involvement from ocular fixational patterns using a deep video representation. Health and Technology. 10.1007/s12553-023-00782-y. 2023-10-03

• Santiago Gómez, Daniel Mantilla, Gustavo Garzón, Edgar Rangel, Andrés Ortiz, Franklin Sierra-Jerez, Fabio Martínez. APIS: A paired CT-MRI dataset for ischemic stroke segmentation challenge. arXiv preprint arXiv:2309.15243.2023

• C.C. Viáfara, B. Valenzuela, F. Martínez, J.J. Penagos. A method to analyze wear mechanisms on worn chute lining surfaces using computer vision tools. Accepted in Tribology International. 2023

• Gómez, S., Mantilla, D., Rangel, E., Ortiz, A., Vera, D. D., & Martínez, F. (2023). A deep supervised cross-attention strategy for ischemic stroke segmentation in MRI studies. Biomedical Physics & Engineering Express, 9(3), 035026.  

• Moreno, A., Olmos, J., Guayacán, L., & Martínez, F. (2023, April). Exploiting Multi-Head Attention Maps Into A Deep Riemannian Representation to Quantify Pulmonary Nodules. In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) (pp. 1-4). IEEE. 

• Gutiérrez, Y., Olmos, J., Guayacán, L., & Martínez, F. (2023, April). A Multimodal Geometric Deep Representation to Support Bi-Parametric Prostate Cancer Lesion Classification. In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) (pp. 1-4). IEEE. 

• Gómez Santiago, Florez Sebastian, Manitlla Daniel, Camacho Paul, Tarazona Nick & Martínez-Carrillo, F. (2023).An attentional Unet with an auxiliary class learning to support acute ischemic stroke segmentation on CT. SPIE-medical imaging. San Diego EEUU

• Moreno Alejandra, Rueda Andrea, & Martínez-Carrillo, F. (2023). A volumetric multi-head attention strategy for lung nodule classification in CT. SPIE-medical imaging. San Diego EEUU

• Catro Santiago, Romo David, Guayacan Luis,  & Martínez-Carrillo, F. (2023). ast detection and localization of mitosis using a semi-supervised deep representation.  SPIE-medical imaging. San Diego EEUU

• Ruiz-García, L. M., Guayacán-Chaparro, L. C., & Martínez-Carrillo, F. (2023). Attention Maps to Highlight Potential Polyps during Colonoscopy. Tecnura, 27(75), 3-3.

• Olmos, J., Galvis, J., & Martínez, F. (2022). Gait Patterns Coded as Riemannian Mean Covariances to Support Parkinson’s Disease Diagnosis. In Ibero-American Conference on Artificial Intelligence (pp. 3-14). Springer, Cham.

• Gutiérrez, Y., Arevalo, J., & Martínez, F. (2022). An inception-based deep multiparametric net to classify clinical significance MRI regions of prostate cancer. Physics in Medicine & Biology, 67(22), 225004.

• Niño, S., Olmos, J. A., Galvis, J. C., & Martínez, F. (2022). Parkinsonian gait patterns quantification from principal geodesic analysis. Pattern Analysis and Applications, 1-11.

• Ruiz, Lina., & Martínez, Fabio. (2022, July). Weakly Supervised Polyp Segmentation from an Attention Receptive Field Mechanism. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 3745-3748). IEEE. 

• Valenzuela, B., Arevalo, J., Contreras, W., & Martinez, Fabio. (2022, July). A Spatio-Temporal Hypomimic Deep Descriptor to Discriminate Parkinsonian Patients. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 4192-4195). IEEE. 

• Sierra-Jerez, F., Ruiz, J., & Martínez, Fabio. (2022, July). A Non-Aligned Deep Representation to Enhance Standard Colonoscopy Observations from Vascular Narrow Band Polyp Patterns. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1671-1674). IEEE  

• Rangel, E., & Martínez, Fabio. (2022, July). A Parkinsonian Digital Biomarker Learned as an Anomaly Deep Generative Representation. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 4188-4191). IEEE. 

• Olmos, J., & Martínez, Fabio. (2022, July). A Riemannian Deep Learning Representation to Describe Gait Parkinsonian Locomotor Patterns. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 3538-3541). IEEE. 

• Garzón, G., Gomez, S., Mantilla, D., & Martínez, Fabio. (2022, July). A deep CT to MRI unpaired translation that preserve ischemic stroke lesions. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2708-2711). IEEE. 

• Gutiérrez, Y., Arevalo, J., & Martánez, F. (2022, July). Multimodal Contrastive Supervised Learning to Classify Clinical Significance MRI Regions on Prostate Cancer. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1682-1685). IEEE. 

•  León, F., & Martínez, F. (2022). A multitask deep representation for Gleason score classification to support grade annotations. Biomedical Physics & Engineering Express, 8(3), 035021.

• Olmos, J., Manzanera, A., Martínez, F. (2022). An Oculomotor Digital Parkinson Biomarker from a Deep Riemannian Representation. In: Pattern Recognition and Artificial Intelligence. ICPRAI 2022. Lecture Notes in Computer Science, vol 13363. Springer, Cham. https://doi.org/10.1007/978-3-031-09037-0_55 

• Moreno, A., Rodríguez, J., & Martínez, F. (2022). Kinematic motion representation in Cine-MRI to support cardiac disease classification. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 10(6), 707-718. 

• Mendoza, O., Martinez, F., & Olmos, J. (2022). A local volumetric covariance descriptor for markerless Parkinsonian gait pattern quantification. Multimedia Tools and Applications, 81(21), 30733-30748. 

• William Omar Contreras López, Luis Guayacan, Fabio Martinez, Paula Alejandra Navarro, Melisa Ibarra Quiñonez, Erich Talamoni Fonoff (2022). "Tremor Quantification Through Event-Based Movement Trajectory Modeling Before and After Unilateral Radiofrequency Sub-Thalamotomy in an 83-Years-Old Parkinson Patient: A Case Report  ". (2022)  WFNS 2022 World Neurosurgery Congress. Abstract in World Neurosurgery. Vol 158. pp. 354

• Guayacán, L. C., Manzanera, A., & Martínez, F. (2022). Quantification of parkinsonian kinematic patterns in body-segment regions during locomotion. Journal of Medical and Biological Engineering, 42(2), 204-215. 

• Moreno, A., Rueda, A., & Martinez, F. (2022, March). A Multi-Scale Self-Attention Network to Discriminate Pulmonary Nodules. In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (pp. 1-4). IEEE. 

• Andrés Gomez, Fabian Leon Perez, Miguel Plazas and Fabio Martínez (2021). "Segmentación multinivel de patrones de Gleason usando representaciones convolucionales en imágenes histopatológicas    ". (2021) Vol. 24, nro. 52, e2132, 2021. Revista tecnologicas.

• Archila, J., Manzanera, A., & Martinez, F. (2022). A multimodal Parkinson quantification by fusing eye and gait motion patterns, using covariance descriptors, from non-invasive computer vision. Computer Methods and Programs in Biomedicine, 215, 106607. 

• Sierra-Jerez, F., & Martínez, F. (2022). A deep representation to fully characterize hyperplastic, adenoma, and serrated polyps on narrow band imaging sequences. Health and Technology, 12(2), 401-413.

• Santiago Gomez, David Romo, and Fabio Martínez (2021). "A digital cardiac disease biomarker from a generative progressive cardiac cine-MRI representation ". (2021) Biomedical Engineering Letters .

• Luis Guayácan, and Fabio Martínez (2021). "Visualising and quantifying relevant parkinsonian gait patterns using 3D convolutional network". (2021) Journal of Biomedical Informatics.

• Miguel Plazas, Raúl Ramos, Fabian León, Fabio Martínez. "Towards reduction of expert bias on Gleason score classification via a semi-supervised deep learning strategy" accepted in SPIE medical imaging 2022

• John Archila, Antoine Manzanera, and Fabio Martínez (2021). "A recurrent approach for predicting Parkinson stage from multimodal videos,"  Accepted in SIPAIM

• Miguel Plazas, Raúl Ramos-Pollán, and Fabio Martínez (2021). "Ensemble-based approach for semisupervised learning in remote sensing," Journal of Applied Remote Sensing 15(3), 034509 (5 August 2021). https://doi.org/10.1117/1.JRS.15.034509 

• Henry Peña, Santiago Gómez, David Romo-Bucheli and and Fabio Martínez (2021). Cardiac Disease Representation Conditioned by Spatio-temporal Priors in Cine-MRI Sequences Using Generative Embedding Vectors. Accepted In 2021 43nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

• Fabian León and Fabio Martínez (2021). Learning a Triplet Embedding Distance to Represent Gleason Patterns. Accepted In 2021 43nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

• Gustavo Garzón and Fabio Martínez. (2021). Local Trajectory Occurrence Patterns for Partial Action and Gesture Recognition. International Journal on Advanced Science, Engineering and Information Technology, Vol. 11 (2021) No. 1, pages: 20-30, DOI:10.18517/ijaseit.11.1.9286

• Rodriguez, J., & Martínez, F. (2021). How important is motion in sign language translation?. IET Computer Vision, 15(3), 224-234.

• Jefferson Rodríguez, David Romo-Bucheli, Franklin Sierra, Diana Valenzuela, Carolina Valenzuela, Lina Vasquez, Paúl Camacho, Daniel Mantilla, Fabio Martínez. (2021). A COVID-19 patient severity stratification using a 3D convolutional strategy on CT-scans. Accepted to ISBI 2021

• Martínez, F., Gouiffès, M., Villamizar, G. G., & Manzanera, A. (2021). A compact and recursive Riemannian motion descriptor for untrimmed activity recognition. Journal of Real-Time Image Processing, 1-14.

• Rodriguez, J., Chacon, J., Rangel, E., Guayacan, L., Hernandez, C., Hernandez, L., & Martinez, F. (2020). Understanding Motion in Sign Language: A New Structured Translation Dataset. In Proceedings of the Asian Conference on Computer Vision.

• Salazar, I.,  Pertuz, S., Contreras, W., & Martínez, F. (2020). A convolutional oculomotor representation to model parkinsonian fixational patterns from magnified videos. Pattern Analysis and Applications.  Pattern Analysis and Applications, 24(2), 445-457. 

• Sierra, F., Gutiérrez, Y., & Martínez, F. (2020, July). An online deep convolutional polyp lesion prediction over Narrow Band Imaging (NBI). In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2412-2415). IEEE.

• Guayacán, L. C., Rangel, E., & Martínez, F. (2020, July). Towards understanding spatio-temporal parkinsonian patterns from salient regions of a 3D convolutional network. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 3688-3691). IEEE.

• Salazar, I., Pertuz, S., & Martínez, F. (2020). Multi-modal RGB-D Image Segmentation from Appearance and Geometric Depth Maps. TecnoLógicas, 23(48), 143-161.

• Salazar, I.,  Pertuz, S., Contreras, W., & Martínez, F. (2019). Parkinsonian Ocular Fixation Patterns from Magnified Videos and CNN Features. CIARP 2019.  In Iberoamerican Congress on Pattern Recognition (pp. 740-750).Springer. 

• León F, S., Plazas M., , & Martínez, F. (2019). An inception deep architecture to differentiate close-related Gleason prostate cancer scores. Proceedings Volume xx, 15th International Symposium on Medical Information Processing and Analysis. spiedigitallibrary

• Gutierrez, Y., Arevalo, J., & Martínez, F. (2019). A K-trans deep characterization to measure clinical significance regions on prostate cancer. Proceedings Volume xx, 15th International Symposium on Medical Information Processing and Analysis. spiedigitallibrary

• Garzón, G., & Martínez, F. (2019, March). Online Action Recognition from Trajectory Occurrence Binary Patterns (ToBPs). In The International Conference on Advances in Emerging Trends and Technologies (pp. 409-418). Springer, Cham.

• Garzón, G., & Martínez, F. (2019). A Fast Action Recognition Strategy Based on Motion Trajectory Occurrences. Pattern Recognition and Image Analysis, 29(3), 447-456. Link. 

• F. Castillo, L. Bautista, Martínez F,  “3d+t  dense motion trajectories as kinematic primitives to recognize gestures on depth video sequences”, Revista Politécnica, vol. 15, no.29 pp.82-94, 2019. DOI: 10.33571/rpolitec.v15n29a7

• Gutierrez Y., Garzón G.,  Martínez F. (2019). Towards clinical significance prediction using $k^{trans}$  evidences in prostate cancer. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

• Moreno A., Rodríguez, J.,  Martínez F. (2019). Regional Multiscale Motion Representation for Cardiac Disease Prediction.  In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

• Valenzuela B., Salazar, I.,  Martínez F. (2019). Lagrangian center of mass (CoM_t) magnification to stand out main parkinsonian gait events. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

• Ruiz L, Guayacan L, Martínez F. (2019). Automatic polyp detection from a regional appearance model and a robust dense Hough coding.  In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

C. Gonzalez, C.C. Viafara, J.J. Coronado, F. Martinez. (2019). Automatic recognition of worn surfaces exhibiting severe and mild abrasive wear regimes. Wear, 426, 1702-1711.

Guayacan, L., Valenzuela, B., & Martínez, F. (2018, Oct). Parkinsonian gait characterization from regional kinematic trajectories. Proceedings Volume 10975, 14th International Symposium on Medical Information Processing and Analysis. spiedigitallibrary.

Moreno, W., Garzón, G., & Martínez, F. (2018, September). Frame-Level Covariance Descriptor for Action Recognition. In Colombian Conference on Computing (pp. 276-290). Springer, Cham.

Rodríguez, J., & Martínez, F. (2018, September). Towards On-Line Sign Language Recognition Using Cumulative SD-VLAD Descriptors. In Colombian Conference on Computing (pp. 371-385). Springer, Cham.

Rodríguez, J., & Martínez, F. (2018, September). A Kinematic Gesture Representation Based on Shape Difference VLAD for Sign Language Recognition. In International Conference on Computer Vision and Graphics (pp. 438-449). Springer, Cham.

Sarmiento, E., Pico, J., & Martinez, F. (2018, April). Cardiac disease prediction from spatio-temporal motion patterns in cine-MRI. In Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on (pp. 1305-1308). IEEE.

Martínez, F., Manzanera, A., & Romero, E. (2017). Spatio-temporal multi-scale motion descriptor from a spatially-constrained decomposition for online action recognition. IET Computer Vision, 11(7), 541-549.

Luis Carlos Guayacan, Martínez, F.(2017). Identificación automática de segmentos corporales utilizando un análisis cinemático de la marcha sin marcadores. Encuentro Internacional en Ciencias de la Salud: El saber y la tecnología al servicio de la vida. Abstract in Revista de la Universidad Industrial de Santander. Salud  Vol.49 No.3 Julio - Septiembre de 2017

A multiresolution prostate representation for automatic segmentation in magnetic resonance images. Alvarez, Charlens and Martínez, Fabio and Romero, Eduardo. Medical Physics, 44 (4), 1312--1323. (2017)

Giraldo-Cadavid, L. F., Agudelo-Otalora, L. M., Burguete, J., Arbulu, M., Moscoso, W. D., Martínez, F., ... & Fernández, S. (2016). Design, development and validation of a new laryngo-pharyngeal endoscopic esthesiometer and range-finder based on the assessment of air-pulse variability determinants. Biomedical engineering online, 15(1), 52.

Martínez, F., Manzanera, A., Gouiffes, M., & Nguyen, T. P. (2015). Action-centric Polar Representation of Motion Trajectories for Online Action Recognition. In International Conference on Computer Vision Theory and Applications (VISAPP).

Martínez, F., Manzanera, A., Gouiffès, M., & Braffort, A. (2015, December). A Gaussian mixture representation of gesture kinematics for on-line Sign Language video annotation. In International Symposium on Visual Computing (pp. 293-303). Springer, Cham.

Setkov, A., Carillo, F. M., Gouiffès, M., Jacquemin, C., Vanrell, M., & Baldrich, R. (2015, December). Dacimpro: A novel database of acquired image projections and its application to object recognition. In International Symposium on Visual Computing (pp. 463-473). Springer, Cham.

Martínez, F., Ruano, J., Gómez, M., & Romero, E. (2015). Estimating the size of polyps during actual endoscopy procedures using a spatio-temporal characterization. Computerized Medical Imaging and Graphics, 43, 130-136.

Martínez, F., Manzanera, A., & Romero, E. (2015). Automatic analysis and characterization of the hummingbird wings motion using dense optical flow features. Bioinspiration & biomimetics, 10(1), 016006.

Martínez, F., Romero, E., Dréan, G., Simon, A., Haigron, P., De Crevoisier, R., & Acosta, O. (2014). Segmentation of pelvic structures for planning CT using a geometrical shape model tuned by a multi-scale edge detector. Physics in Medicine & Biology, 59(6), 1471.

Martinez, F., Gómez, F., & Romero, E. (2011). A kinematic method for computing the motion of the body centre-of-mass (CoM) during walking: a Bayesian approach. Computer methods in biomechanics and biomedical engineering, 14(06), 561-572.

Cárdenas, L., Martínez, F., Atehortúa, A., & Romero, E. (2015, December). Quantifying Parkinson's disease progression by simulating gait patterns. In 11th International Symposium on Medical Information Processing and Analysis (Vol. 9681, p. 96810J). International Society for Optics and Photonics.

Trujillo, D., Martínez, F., Atehortúa, A., Alvarez, C., & Romero, E. (2015, December). A characterization of Parkinson's disease by describing the visual field motion during gait. In 11th International Symposium on Medical Information Processing and Analysis (Vol. 9681, p. 96810K). International Society for Optics and Photonics.

Atehortúa, A., Zuluaga, M. A., Martínez, F., Ourselin, S., & Romero, E. (2015, December). Automatic right ventricle (RV) segmentation by propagating a basal spatio-temporal characterization. In 11th International Symposium on Medical Information Processing and Analysis (Vol. 9681, p. 96810N). International Society for Optics and Photonics.

Sarmiento, F., Atehortúa, A., Martínez, F., & Romero, E. (2015, December). Ipsilateral coordination features for automatic classification of Parkinson's disease. In 11th International Symposium on Medical Information Processing and Analysis (Vol. 9681, p. 96810L). International Society for Optics and Photonics.

Infante, K., Martinez, F., & Arbulu, M. (2014). Robot navigation by fusing a spatio-temporal video descriptor with a robust humanoid motion control for kicking a ball. 9th Workshop on Humanoid Soccer Robots. Madrid-Spain.

Ruano, J., Martínez, F., Gómez, M., & Romero, E. (2015, January). A 3D endoscopy reconstruction as a saliency map for analysis of polyp shapes. In 10th International Symposium on Medical Information Processing and Analysis (Vol. 9287, p. 928718). International Society for Optics and Photonics. 

Cárdenas, L., Martínez, F., & Romero, E. (2015, January). Simulation of Parkinsonian gait by fusing trunk learned patterns and a lower limb first order model. In 10th International Symposium on Medical Information Processing and Analysis (Vol. 9287, p. 92871B). International Society for Optics and Photonics. 

Álvarez, C., Martínez, F., & Romero, E. (2015, January). An automatic multi-atlas prostate segmentation in MRI using a multiscale representation and a label fusion strategy. In 10th International Symposium on Medical Information Processing and Analysis (Vol. 9287, p. 92870D). International Society for Optics and Photonics. 

Sarmiento, F., Martínez, F., & Romero, E. (2015, January). Automatic characterization of the Parkinson disease by classifying the ipsilateral coordination and spatiotemporal gait patterns. In 10th International Symposium on Medical Information Processing and Analysis (Vol. 9287, p. 928719). International Society for Optics and Photonics. 

Trujillo, D., Martínez, F., & Romero, E. (2015, January). Characterizing the eye trajectory during the gait towards Parkinson stage identification. In 10th International Symposium on Medical Information Processing and Analysis(Vol. 9287, p. 92871A). International Society for Optics and Photonics. 

Martínez, F., Manzanera, A., & Romero, E. (2014, March). Representing activities with layers of velocity statistics for multiple human action recognition in surveillance applications. In Video Surveillance and Transportation Imaging Applications 2014 (Vol. 9026, p. 90260G). International Society for Optics and Photonics. 

Labrador, A. M. A., Martínez, F., & Castro, E. R. (2013, November). A novel right ventricle segmentation approach from local spatio-temporal MRI information. In Iberoamerican Congress on Pattern Recognition (pp. 206-213). 

Ruano, J., Martinez, F., Gomez, M., & Romero, E. (2013, November). Shape estimation of gastrointestinal polyps using motion information. In IX International Seminar on Medical Information Processing and Analysis (Vol. 8922, p. 89220N). International Society for Optics and Photonics. 

Atehortúa, A., Martínez, F., & Romero, E. (2013, November). A novel right ventricle segmentation strategy using local spatio-temporal MRI information with a prior regularizer term. In IX International Seminar on Medical Information Processing and Analysis (Vol. 8922, p. 892203). International Society for Optics and Photonics. 

Álvarez, C., Martínez, F., & Romero, E. (2013, November). A novel atlas-based approach for MRI prostate segmentation using multiscale points of interest. In IX International Seminar on Medical Information Processing and Analysis (Vol. 8922, p. 89220O). International Society for Optics and Photonics.

Martínez, F., Manzanera, A., & Romero, E. (2012). A motion descriptor based on statistics of optical flow orientations for action classification in video-surveillance. In Multimedia and Signal Processing (pp. 267-274). 

Martinez, F., Manzanera, A., & Romero, E. (2012, November). Analysing the hovering flight of the hummingbird using statistics of the optical flow field. In ICPR workshop on Visual observation and analysis of animal and insect behavior. 

Martinez, F., Acosta, O., Dréan, G., Simon, A., Haigron, P., De Crevoisier, R., & Romero, E. (2012). Segmentation of pelvic structures from planning CT based on a statistical shape model with a multiscale edge detector and geometrical likelihood measures. Image-Guidance and Multimodal Dose Planning in Radiation Therapy, 26. 

León J, Martinez, F., & Romero, E. (2012). A robust background subtraction algorithm using a Sigma-Delta estimation. In International Conference on Computer Vision Theory and Applications (Visapp). Rome - Italy.

Cifuentes F,  Martinez, F., & Romero, E. (2012). A 3D physics-based model to simulate normal and pathological gait patterns. In . International Conference on Computer Graphics Theory and Applications (GRAPP). Rome - Italy. 

Martinez, F., León J, & Romero, E. (2011).  Pathology Classification of Gait Human Gestures. International Conference on Computer Vision Theory and Applications (Visapp).  Algarve - Portugal (2011) 

Martínez, F., Manzanera, A., Santa Marta, C., & Romero, E. (2011, November). Characterization of motion cardiac patterns in magnetic resonance cine. In 2011 International Conference on Image Information Processing (pp. 1-5). IEEE. 

Martínez, F., Acosta, O., de Crevoisier, R., & Romero, E. (2012). Local jet features and statistical models in a hybrid Bayesian framework for prostate estimation in CBCT images. In Medical Imaging 2012: Computer-Aided Diagnosis(Vol. 8315, p. 83151R). International Society for Optics and Photonics. 

Gómez, F., Martínez, F., & Romero, E. (2010). Predicting Complex Patterns of Human Movements Using Bayesian Online Learning in Medical Imaging Applications. In Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques (pp. 283-306). IGI Global. 

Martínez, F., Gómez, F., & Romero, E. (2009). Análisis de vídeo para estimación del movimiento humano: una revisión. Revista Med, 17(1). 

Martínez F., Jaramillo, F. G., & Romero, E. (2010). Desarrollo de un laboratorio de marcha con integracion sincronica mediante una arquitectura en modulos. Acta biológica colombiana, 15(3), 235-250. 

Cifuentes, C., Martínez, F., & Romero, E. (2010). Análisis teórico y computacional de la marcha normal y patológica: una revisión. Revista Med, 18(2), 182-196. 

Martínez F,  Gómez F,  Romero E. (2009) Computational Method for Tracking the Body Center of Mass(CoM) during the Gait: A Bayesian Approach. En: SIB-SIPAIM:  2009.

Pinzón A., Martínez F., Romero E. (2010). Análisis Experimental de la Extracción del Esqueleto por Contracción con Suavizado Laplaciano. SIPAIM: VI Seminario Internacional de Procesamiento y Análisis de Imágenes Médicas (2010). 

León J,  Martínez F,  Romero E. (2010). Classification of Pathological Gait Markerless Pattern. SIPAIM: VI Seminario Internacional de Procesamiento y Análisis de Imágenes Médicas. Bogotá. Colombia (2010). 

León J,  Martínez F,  Romero E. (2011). A Comparison of Σ − ∆ Background Substraction Algorithms for Gait Analysis. (2011). SIPAIM: VII Seminario Internacional de Procesamiento y Análisis de Imágenes Médicas. Bucaramanga. Colombia (2011). 

Cifuentes C,  Martínez F,  Romero E. (2011). Physics-based model to simulate the Parkinsonian gait. SIPAIM: VII Seminario Internacional de Procesamiento y Análisis de Imágenes Médicas. Bucaramanga. Colombia (2011). 

Mosquera C,  Martínez F,  Acosta O, Crevoisier R,  Romero E. Prostate Localization Using a Probabilistic Model. (2011). SIPAIM: VII Seminario Internacional de Procesamiento y Análisis de Imágenes Médicas. Buc. Colombia (2011). 

Martínez F,  Gómez F,  Romero E. (2008) Arquitectura Modular para Laboratorios Clínicos de Marcha.  III Congreso de BioIngeniería e Ingeniería BIomédica. Pereira. Colombia.