Publications

• Sarmiento-Rojas, J., Aya-Parra, P.A., and Perdomo, O.J. (2022), Proposal of Design and Innovation in the Creation of the Internet of Medical Things Based on the CDIO Model through the Methodology of Problem-Based Learning. Sensors 22, 8979. https://0-doi-org.brum.beds.ac.uk/10.3390/s22228979

• Padilla, F.D., Sanchez, Y.D., Quijano-Nieto, B.A., Perdomo, O.J., and González, F.A.(2022), Etiology of Macular Edema Defined by Deep Learning in Optical Coherence Tomography Scans. Translational vision science & technology 11 (9). https://doi.org/10.1167/tvst.11.9.29

• Pascal, L., Perdomo, O.J., Bost, X., Huet, B., Otálora, S., Zuluaga, M.A. (2022), Multi-task Deep Learning for Glaucoma Detection from Color Fundus Images, Scientific Reports 12, 12361. doi.org/10.1038/s41598-022-16262-8

• Cruz, B.S., Aguía, K., Perdomo, O.J. (2021), Monitoring and Evaluation of People in Indoors and Outdoors Using Deep Learning, In 17th International Symposium on Medical Information Processing and Analysis. doi:0.1117/12.2606334

• De la Pava, M., Perdomo, O.J., González, F.A. (2021), A Deep Learning Model for Classification of Diabetic Retinopathy in Eye Fundus Images Based on Retinal Lesion Detection, In 17th International Symposium on Medical Information Processing and Analysis. doi:10.1117/12.2606319

• Orjuela, A.D., Perdomo, O.J., Mendoza, L., Valencia, C.H. (2021), Intensive Care Unit Occupancy Time Series Forecasting for COVID-19 Pandemic, 2nd International Congress of Biomedical Engineering & Bioengineering (CI-IB&BI). doi:978-1-6654-0855-4/21/

• Orjuela, A.D., Perdomo, O.J. (2021), Modelación de Series de Tiempo para la Predicción del Uso de Camas de Unidades de Cuidado Intensivo Asociado a la COVID-19, Biomédica - Revista del Instituto Nacional de Salud, 41(3). https://revistabiomedica.org/index.php/biomedica/issue/view/184

• Arango, M.L., Giraldo, L.F., Perdomo, O.J. (2021), Electroestimulador Diafragmático con Control Automatizado de la Ventilación Mínuo para Ajustarla a las Necesidades Fisiológicas del Individuo, Encuentro Internacional de Educación en Ingeniería (EIEI) - ACOFI 2021. https://www.acofi.edu.co/eiei2021/

• Pinto, M.J., Cifuentes, C.A., Perdomo, O.J., Rincón, M., Múnera, M. (2021), A Data-Driven Approach to Physical Fatigue Management Using Wearable Sensors to Classify Four Diagnostic Fatigue States, Sensors, 21(19), 6401. doi:10.3390- /s21196401

• Aguirre, A., Pinto, M.J., Cifuentes, C.A., Perdomo, O.J., Múnera, M. (2021), Machine Learning Approach for Fatigue Estimation in Sit-to-Stand Exercise, Sensors, 21(15), 5006 (pp. 1-31). https://www.mdpi.com/1424-8220/21/15/5006. doi:10.3390/s21155006

• Perdomo, O.J., Orjuela, A.D., Toledo, S., González, F.A. (2021), What You Need to Know About Artificial Intelligence: Technical Introduction, Artificial Intelligence and Ophthalmology: Perks, Perils and Pitfalls, In Parul Ichhpujani (Eds.) (pp. 13-25). doi:10.1007/978-981-16-0634-2\_2

• Orjuela, A.D, Perdomo, O.J. (2021), Clustering Proposal Support for the COVID-19 Making Decision Process in a Data Demanding Scenario, IEEE Latin America Transactions. doi: 10.1109/TLA.2021.9451250

• Pérez, A., Ríos, H., Rodríguez, F.,Perdomo, O.J., González, F.A. (2020), A Conditional Generative Adversarial Network-based Method for Eye Fundus Image Quality Enhancement, Proceedings of the Ophthalmic Medical Image Analysis Seventh International Workshop (MICCAI 2020). doi:10.1007/978-3-030-63419-3\_19

• Toledo, S., De la Pava, M.,Perdomo, O.J., González, F.A. (2020), Hybrid Deep Learning Gaussian Process for Diabetic Retinopathy Diagnosis and Uncertainty Quantification, Proceedings of the Ophthalmic Medical Image Analysis Seventh International Workshop (MICCAI 2020). doi:10.1007/978-3-030-63419-3\_21

• Perdomo, O.J., Pérez. A.D., De la Pava, M., Ríos, H.A., Arias, V.A., Lara, J.S., Camargo, J.E., Rodríguez, F.J., González, F.A. (2020), SOPHIA: System  for Ophthalmic Image Acquisition, Transmission, and Intelligent Analysis, Revista Facultad de Ingeniería UPTC. doi:10.19053/01211129.v29.n54.2020.11769

• Sánchez, Y., Nieto, B., Padilla, F.D., Perdomo, O.J., González, F. (2020), Segmentation of Retinal Fluids and Hyperreflective Foci Using Deep Learning Approach in Optical Coherence Tomography Scans, In 16th International    Symposium on Medical Information Processing and Analysis. doi:10.1117/12.2579934

• Calvache, D., Bernal, H.A., Guarín. J.F., Aguía, K., Orjuela, A., Perdomo, O.J. (2020), Automatic Estimation of Pose and Falls in Videos Using Computer Vision Model, In 16th International Symposium on Medical Information Processing and Analysis. doi:10.1117/12.2579615

• Navas, M., Orjuela, A. Perdomo, O.J. (2020), Comparison of Machine Learning Models for the Prediction of Cancer Cells using MHC Class I Complexes, In 16th International Symposium on Medical Information Processing and Analysis. doi:10.1117/12.2579602

• Orjuela, A.,Perdomo, O.J., Valencia, C., Forero, L. (2020), Convolutional Neural Network Proposal for Wrist Position Classification from Electromiography Signals, In Applications of Computational Intelligence: Third IEEE Colombian Conference, ColCACI 2020. doi:10.1109/ColCACI50549.2020.9247924

• Pérez, A. D., Perdomo, O.J. & González, F. (2020), A Lightweight Deep Learning Model for Mobile Eye Fundus Image Quality Assessment, In 15th International Symposium on Medical Information Processing and Analysis. doi:10.1117/12.2547126

• Perdomo, O.J., González, F.A. (2020), A Systematic Review of Deep Learning Methods Applied to Ocular Images, Ciencia e Ingeniería Neogranadina, 30. doi:10.18359/rcin.4242

• Perdomo, O.J., Ríos, H., Rodríguez, F. J., Otálora, S., Meriaudeau, F., Müller, H., González, F.A. (2019), Classification of Diabetes-Related Retinal Diseases using a Deep Learning Approach in Optical Coherence Tomography, Computer Methods and Programs in Biomedicine, 178. doi:10.1016/j.cmpb.2019.06.016

• Pinzón, O., García, C., Perdomo, O.J., Nuñez, A., Córdoba, N.P., Beltrán, A., Sarmiento-Rojas, J., Quiroga-Torres, D.A., Aya-Parra, P.A. (2019), Monitoring of Critical Variables in the Imaging Service from the Internet of Things (IoT), In Latin American Conference on Biomedical Engineering. doi:10.1007/978-3-030-30648-9\_171

• Rodríguez, A.C., Gómez, E.A., Perdomo, O.J. (2018), Breathing and Temperature Detection using Thermal Images in Infants, Visión electrónica, 1(2),  Special  edition, (pp.1-18). doi:10.14483/issn.2248-4728

• Wilches, C.A., Perdomo, C.A., Perdomo, O.J. (2018), A Method to Detect Potentially Malignant Skin Lesions through Image Segmentation, In World Congress on Medical Physics and Biomedical Engineering 2018 (pp. 289-293). Springer. doi:10.1007/978-981-10-9035-6\_52

• Perdomo, O.J., Otálora, S., González, F.A., Meriaudeau, F., Müller, H. (2018), Oct-net: A Convolutional Network for Automatic Classification of Normal and Diabetic Macular Edema using SD-OCT Volumes, IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018). doi:10.1109/ISBI.2018.8363839

• Otálora, S., Perdomo, O.J., Atzori, M., Andersson, M., Jacobsson, L., Hedlund, M., Müller, H. (2018), Determining the Scale of Image Patches using a Deep Learning Approach, In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018). doi:10.1109/ISBI.2018.8363703

• Kamble, R. M., Chan, G. C., Perdomo, O.J., Kokare, M., González, F. A., Müller, H., Mériaudeau, F. (2018), Automated Diabetic Macular Edema (DME) Analysis using Fine Tuning with Inception-Resnet-v2 on OCT Images, In 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES). doi:10.1109/IECBES.2018.8626616

• Perdomo, O.J., Andrearczyk, V., Meriaudeau, F., Müller, H., González, F.A. (2018), Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation, In Computational Pathology and Ophthalmic Medical Image Analysis (MICCAI 2018), Springer, Cham. doi:10.1007/978-3-030-00949-6\_38

• Perdomo, O.J., Rios, H. A., Rodríguez, F. J., González, F. A., (2018). 3D Deep Convolutional Neural Network for Predicting Neurosensory Retinal Thickness Map from Spectral Domain Optical Coherence Tomography Volumes, In 14th International Symposium on Medical Information Processing and Analysis, International Society for Optics and Photonics. doi:10.1117/12.\\2511597

• Contreras, V. H., Lara, J. S., Perdomo, O.J., González, F. A., (2018). Supervised Online Matrix Factorization for Histopathological Multimodal Retrieval, In 14th International Symposium on Medical Information Processing and Analysis, International Society for Optics and Photonics. doi:10.1117/12.2513352

• Rodríguez, A. C., Gómez, E., & Perdomo, O.J. (2018). Non-Invasive Model for Detection of Extrinsic Risk Factor of Sudden Infant Death Syndrome, International Journal of Applied Engineering Research 13(19). doi:ijaer18/ijaerv13n19_19

• Cifuentes, C., Argothy, R. & Perdomo, O.J. (2017), Patrones Biomecánicos de Referencia para el Diagnóstico Temprano de Trastornos del Equilibrio: Estudio piloto, Revista Mexicana de Ingeniería Biomédica. doi:10.17488/rmib.38.1.6

• Otálora, S., Perdomo, O.J., González, F., Müller, H. (2017), Training Deep Convolutional Neural Networks with Active Learning for Exudate Classification in Eye Fundus Images, In Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (MICCAI 2017). doi:10.1007/978-3-319-67534-3\_16

• Perdomo, O.J., Arévalo, J., González, F.A. (2017), Combining Morphometric Features and Convolutional Networks Fusion for Glaucoma Diagnosis, In 13th International Symposium on Medical Information Processing and Analysis, International Society for Optics and Photonics. doi:10.1117/12.2285964

• Perdomo, O.J., Otálora, S., Rodríguez, F., Arévalo, J., González, F.A. (2016), A Novel Machine Learning Model Based on Exudate Localization to Detect Diabetic Macular Edema, Proceedings of the Ophthalmic Medical Image Analysis Third International Workshop (MICCAI 2016). doi:10.17077/omia.1057

• Perdomo, O.J., Arévalo, J., González, F.A. (2016), Convolutional Network to Detect Exudates in Eye Fundus Images of Diabetic Subjects, In 12th International Symposium on Medical Information Processing and Analysis, International Society for Optics and Photonics. doi:10.1117/12.2256939

• Šeketa, G., Ortiz, G., Wilches, C., Perdomo, O.J., Celić, L., Lacković, I., Zequera, M. and Magjarević, R. (2015). Simultaneous measurement of trunk orientation and centre of pressure for postural stability evaluation. In 6th European Conference of the International Federation for Medical and Biological Engineering (pp. 363-366). Springer, Cham. doi:10.1007/978-3-319-11128-5_91

• Zequera, M., Perdomo, O.J., Wilches, C. & Vizcaya, P. (2013). Pilot study: Biomechanical assessment of the plantar pressure distribution in healthy subjects using the pressure platform EcoWalk. International Journal of Engineering and Technology, 13(6), pp.97-101. doi:10.1088/1742-6596/450/1/012029

• Zequera, M.,  Perdomo, O.J., Wilches, C. and Vizcaya, P. (2013). Pilot study: Assessing repeatability of the EcoWalk platform resistive pressure sensors to measure plantar pressure during barefoot standing. In Journal of Physics: Conference Series 450, (1). IOP Publishing. doi:10.1088/1742-6596/450/1/012029

• Perdomo, O.J., Perdomo, C.A. and Marques, J.L. (2013). Modeling and simulation of ventricular repolarization or T-wave of ECG of subjects with type 1 diabetes during adrenaline infusions. In 2013 Pan American Health Care Exchanges (PAHCE) (pp. 1-6). IEEE. doi:10.1109/PAHCE.2013.6568237

• Perdomo, O.J., Robinson, E.J., Heller, S.R. and Marques, J.L. (2012). A Qualitative Model to Assess the Cardiac Repolarization Alterations During Adrenaline Infusions. In XXIII Congresso Brasileiro em Engenharia Biomédica - CBEB 2012.

• Perdomo, O.J., Robinson, E.J., Suzuki, D.O., Heller, S.R. and Marques, J.L. (2012). Morphological analysis of T-wave in vectorcardiographic leads system by a bi-Gaussian approach in patients under effect of salbutamol. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 5494-5497). IEEE. doi:10.1109/EMBC.2012.6347238

Software & Patents

🏆 [Patent record: NC2022/0013103, 🇨🇴]] - Diaphragmatic electrostimulator.

🏆 [Patent record: NC2022/0006568, 🇨🇴] - Portable eye examination equipment with handling and clamping systems adaptable to image capture devices.

🏆 [Patent record: NC2021/0015179, 🇨🇴] - Device for the measurement of maximum inspiratory and expiratory static pressure.

🏆 [Patent record: NC2018/0014415, 🇨🇴] - Procedure for non-invasive monitoring of temperature, breathing and position in babies using thermal images.

💻 [Software record: 13-94-477, 🇨🇴] - Interactive platform for learning and running Python code for healthcare personnel. 

💻 [Software record: 13-94-476, 🇨🇴] - Platform for movement characterization using computer vision and information from inertial sensors. 

💻 [Software record: 13-94-475, 🇨🇴] - Application for detection and analysis of micro-sleep. 

💻 [Software record: 13-87-258, 🇨🇴] - Ophthalmology diagnostic image transmission, storage and analysis platform (PAIDO). 

💻 [Software record: 13-75-76, 🇨🇴] - Software to remotely control televisions for people with reduced mobility in upper limbs through bioelectric potentials. 

💻 [Software record: 13-74-287, 🇨🇴] - Interface for BCI-MBOT Ranger Open BCI - Practice interaction. 

💻 [Software record: 13-70-35, 🇨🇴] - Software for the automatic estimation of the Hernández-Corvo index for evaluation of plantar pressure. 

💻 [Software record: 13-68-246, 🇨🇴] - Application for the analysis of sudden infant death syndrome. 

💻 [Software record: 13-62-200, 🇨🇴] - Occlusal force measurement device. 

💻 [Software record: 13-55-326, 🇨🇴] - Design and development of prototype for tests of push-up arm bends by means of sensor conditioning and EMG analysis. 

💻 [Software record: 13-53-328, 🇨🇴] - Heart-Carter Somatotype Analysis. 

💻 [Software record: 13-49-320, 🇨🇴] - Romberg Test Analysis. 

Contact ➡️ e-mail: ojperdomoc@unal.edu.co