Marcos Ortega

3.2k total citations
151 papers, 1.9k citations indexed

About

Marcos Ortega is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Marcos Ortega has authored 151 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 111 papers in Radiology, Nuclear Medicine and Imaging, 76 papers in Ophthalmology and 34 papers in Computer Vision and Pattern Recognition. Recurrent topics in Marcos Ortega's work include Retinal Imaging and Analysis (91 papers), Retinal Diseases and Treatments (49 papers) and Glaucoma and retinal disorders (40 papers). Marcos Ortega is often cited by papers focused on Retinal Imaging and Analysis (91 papers), Retinal Diseases and Treatments (49 papers) and Glaucoma and retinal disorders (40 papers). Marcos Ortega collaborates with scholars based in Spain, Netherlands and Chile. Marcos Ortega's co-authors include Jorge Novo, Manuel G. Penedo, José Rouco, Joaquim de Moura, Álvaro S. Hervella, N. Barreira, Marı́a J. Carreira, Lucía Ramos, Francisco Gómez‐Ulla and Brais Cancela and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

Marcos Ortega

138 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Marcos Ortega Spain 24 1.2k 735 461 302 278 151 1.9k
Muthu Rama Krishnan Mookiah Singapore 23 1.4k 1.1× 790 1.1× 597 1.3× 219 0.7× 220 0.8× 50 1.9k
Anjan Gudigar India 27 952 0.8× 320 0.4× 633 1.4× 243 0.8× 457 1.6× 58 2.0k
Manuel G. Penedo Spain 23 1.0k 0.9× 751 1.0× 594 1.3× 204 0.7× 273 1.0× 121 1.9k
Kuang Chua Chua Singapore 17 653 0.5× 410 0.6× 368 0.8× 208 0.7× 197 0.7× 31 1.6k
Chua Kuang Chua Singapore 28 1.4k 1.1× 898 1.2× 786 1.7× 241 0.8× 405 1.5× 36 2.7k
Sulatha V. Bhandary India 27 2.0k 1.6× 1.6k 2.2× 1.1k 2.3× 165 0.5× 197 0.7× 71 2.5k
Radim Bürget Czechia 22 557 0.5× 280 0.4× 554 1.2× 224 0.7× 443 1.6× 139 1.8k
Muhammad Sharif Pakistan 32 874 0.7× 232 0.3× 928 2.0× 227 0.8× 947 3.4× 44 2.6k
Carlos A. Silva Portugal 20 1.1k 0.9× 208 0.3× 1.6k 3.4× 377 1.2× 836 3.0× 55 3.1k
Ruogu Fang United States 18 662 0.5× 307 0.4× 590 1.3× 181 0.6× 273 1.0× 71 1.6k

Countries citing papers authored by Marcos Ortega

Since Specialization
Citations

This map shows the geographic impact of Marcos Ortega's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marcos Ortega with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcos Ortega more than expected).

Fields of papers citing papers by Marcos Ortega

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcos Ortega. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marcos Ortega. The network helps show where Marcos Ortega may publish in the future.

Co-authorship network of co-authors of Marcos Ortega

This figure shows the co-authorship network connecting the top 25 collaborators of Marcos Ortega. A scholar is included among the top collaborators of Marcos Ortega based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marcos Ortega. Marcos Ortega is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Herrero, Pau, et al.. (2025). Inter-expert reliability in multi-field-of-view automatic drusen segmentation analysis using optical coherence tomography. Biomedical Signal Processing and Control. 112. 108476–108476.
2.
Ortega, Marcos, Víctor Mangas‐Sanjuán, Miguel González‐Barcia, et al.. (2024). Artificial Intelligence and Machine Learning Applications to Pharmacokinetic Modeling and Dose Prediction of Antibiotics: A Scoping Review. Antibiotics. 13(12). 1203–1203. 1 indexed citations
3.
García‐Porta, Nery, et al.. (2024). Are artificial intelligence chatbots a reliable source of information about contact lenses?. Contact Lens and Anterior Eye. 47(2). 102130–102130. 3 indexed citations
4.
Heras, Jónathan, et al.. (2024). Deep Learning Models for Justified Referral in AI Glaucoma Screening. 1–3. 1 indexed citations
5.
Moura, Joaquim de, et al.. (2023). Automatic simultaneous ciliary muscle segmentation and biomarker extraction in AS-OCT images using deep learning-based approaches. Biomedical Signal Processing and Control. 90. 105851–105851. 3 indexed citations
6.
Hervella, Álvaro S., Lucía Ramos, José Rouco, Jorge Novo, & Marcos Ortega. (2023). Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity. Medical & Biological Engineering & Computing. 62(3). 865–881. 7 indexed citations
7.
Moura, Joaquim de, et al.. (2023). Multivendor fully automatic uncertainty management approaches for the intuitive representation of DME fluid accumulations in OCT images. Medical & Biological Engineering & Computing. 61(5). 1209–1224. 3 indexed citations
8.
Carmona, Enrique J., et al.. (2023). Deformable registration of multimodal retinal images using a weakly supervised deep learning approach. Neural Computing and Applications. 35(20). 14779–14797. 6 indexed citations
9.
Gende, Mateo, Joaquim de Moura, José Ignacio Fernández‐Vigo, et al.. (2023). Robust multi-view approaches for retinal layer segmentation in glaucoma patients via transfer learning. Quantitative Imaging in Medicine and Surgery. 13(5). 2846–2859. 10 indexed citations
10.
Moura, Joaquim de, et al.. (2020). Deep Convolutional Approaches for the Analysis of COVID-19 Using Chest X-Ray Images From Portable Devices. IEEE Access. 8. 195594–195607. 59 indexed citations
11.
Ramos, Lucía, et al.. (2020). Fully Automatic Retinal Vascular Tortuosity Assessment Integrating Domain-Related Information. SHILAP Revista de lepidopterología. 32–32.
12.
Carmona, Enrique J., et al.. (2020). Modeling, Localization, and Segmentation of the Foveal Avascular Zone on Retinal OCT-Angiography Images. IEEE Access. 8. 152223–152238. 3 indexed citations
13.
Moura, Joaquim de, et al.. (2020). Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks. SHILAP Revista de lepidopterología. 31–31. 1 indexed citations
14.
Rouco, José, et al.. (2019). An end-to-end deep learning approach for simultaneous background modeling and subtraction.. British Machine Vision Conference. 266. 25 indexed citations
15.
Moura, Joaquim de, et al.. (2019). Computerized tool for identification and enhanced visualization of Macular Edema regions using OCT scans.. The European Symposium on Artificial Neural Networks. 1 indexed citations
16.
Rouco, José, et al.. (2019). Blind-spot network for image anomaly detection: A new approach to diabetic retinopathy screening.. The European Symposium on Artificial Neural Networks. 3 indexed citations
17.
Bolón‐Canedo, Verónica, et al.. (2015). On the use of machine learning techniques for the analysis of spontaneous reactions in automated hearing assessment. The European Symposium on Artificial Neural Networks. 1 indexed citations
18.
Dibeklioğlu, Hamdi, et al.. (2010). An Affect-Responsive Interactive Photo Frame. UvA-DARE (University of Amsterdam). 58–68. 1 indexed citations
19.
Mariño, C., et al.. (2008). Automated three stage red lesions detection in digital color fundus images. WSEAS Transactions on Computers archive. 7(4). 207–215. 9 indexed citations
20.
García-Sánchez, Antonio-Javier, et al.. (2006). Computer based tool for temporal and spectral analysis of electrocardiographic records. Digital Repository (Universidad Politécnica de Cartagena). 585–588.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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