Fabio Martínez

575 total citations
82 papers, 317 citations indexed

About

Fabio Martínez is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Fabio Martínez has authored 82 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 19 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Biomedical Engineering. Recurrent topics in Fabio Martínez's work include Radiomics and Machine Learning in Medical Imaging (15 papers), Parkinson's Disease Mechanisms and Treatments (13 papers) and Medical Image Segmentation Techniques (11 papers). Fabio Martínez is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), Parkinson's Disease Mechanisms and Treatments (13 papers) and Medical Image Segmentation Techniques (11 papers). Fabio Martínez collaborates with scholars based in Colombia, France and Brazil. Fabio Martínez's co-authors include Eduardo Romero, Antoine Manzanera, John Arévalo, J.J. Coronado, Pascal Haigron, Oscar Acosta, R. de Crevoisier, Antoine Simon, Daniel Mantilla and Said Pertuz and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Physics in Medicine and Biology.

In The Last Decade

Fabio Martínez

71 papers receiving 297 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fabio Martínez Colombia 9 87 85 64 51 42 82 317
Koray Açıcı Türkiye 11 104 1.2× 118 1.4× 42 0.7× 81 1.6× 45 1.1× 36 438
Tunç Aşuroğlu Türkiye 11 77 0.9× 101 1.2× 51 0.8× 108 2.1× 63 1.5× 47 475
José Bernal United Kingdom 13 148 1.7× 63 0.7× 129 2.0× 101 2.0× 41 1.0× 27 477
K. Meenakshi India 7 79 0.9× 48 0.6× 114 1.8× 97 1.9× 6 0.1× 27 366
María Trujillo Colombia 10 75 0.9× 62 0.7× 47 0.7× 62 1.2× 9 0.2× 42 286
Jiaxi Hu China 12 92 1.1× 50 0.6× 109 1.7× 9 0.2× 14 0.3× 27 431
Zhenwei Zhang United States 11 43 0.5× 47 0.6× 73 1.1× 57 1.1× 9 0.2× 26 427
Xu Tian China 10 23 0.3× 46 0.5× 17 0.3× 36 0.7× 17 0.4× 72 317
Shakhnoza Muksimova South Korea 12 128 1.5× 22 0.3× 56 0.9× 86 1.7× 9 0.2× 32 311

Countries citing papers authored by Fabio Martínez

Since Specialization
Citations

This map shows the geographic impact of Fabio Martínez'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 Fabio Martínez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabio Martínez more than expected).

Fields of papers citing papers by Fabio Martínez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fabio Martínez. 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 Fabio Martínez. The network helps show where Fabio Martínez may publish in the future.

Co-authorship network of co-authors of Fabio Martínez

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Martínez. A scholar is included among the top collaborators of Fabio Martínez 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 Fabio Martínez. Fabio Martínez 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.
Gómez, Francisco Javier, et al.. (2025). A persistent homology gait analysis for Parkinson disease characterization. Biomedical Signal Processing and Control. 106. 107752–107752. 1 indexed citations
2.
Martínez, Fabio, et al.. (2024). Parkinsonian gait modelling from an anomaly deep representation. Multimedia Tools and Applications. 84(19). 21605–21623. 3 indexed citations
3.
Manzanera, Antoine, et al.. (2024). A Riemannian multimodal representation to classify parkinsonism-related patterns from noninvasive observations of gait and eye movements. Biomedical Engineering Letters. 15(1). 81–93. 1 indexed citations
4.
Arévalo, John, et al.. (2024). A contrastive weakly supervised learning to characterize malignant prostate lesions in BP-MRI. Biomedical Signal Processing and Control. 96. 106584–106584. 1 indexed citations
5.
Martínez, Fabio, et al.. (2024). A self-supervised deep Riemannian representation to classify parkinsonian fixational patterns. Artificial Intelligence in Medicine. 157. 102987–102987.
6.
Martínez, Fabio, et al.. (2024). A non-aligned translation with a neoplastic classifier regularization to include vascular NBI patterns in standard colonoscopies. Computers in Biology and Medicine. 170. 108008–108008.
7.
Martínez, Fabio, et al.. (2024). A Volumetric Deep Architecture to Discriminate Parkinsonian Patterns from Intermediate Pose Representations. International journal of psychological research. 17(2). 84–90. 1 indexed citations
8.
Martínez, Fabio, et al.. (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. 38. 107952–107952. 1 indexed citations
9.
Mantilla, Daniel, et al.. (2023). A deep supervised cross-attention strategy for ischemic stroke segmentation in MRI studies. Biomedical Physics & Engineering Express. 9(3). 35026–35026. 5 indexed citations
10.
Martínez, Fabio, et al.. (2023). A method to analyze wear mechanisms on worn chute lining surfaces using computer vision tools. Tribology International. 186. 108586–108586. 5 indexed citations
11.
Martínez, Fabio, et al.. (2022). A deep representation to fully characterize hyperplastic, adenoma, and serrated polyps on narrow band imaging sequences. Health and Technology. 12(2). 401–413. 3 indexed citations
12.
Arévalo, John, et al.. (2022). An inception-based deep multiparametric net to classify clinical significance MRI regions of prostate cancer. Physics in Medicine and Biology. 67(22). 225004–225004. 5 indexed citations
13.
Galvis, Juan, et al.. (2022). Parkinsonian gait patterns quantification from principal geodesic analysis. Pattern Analysis and Applications. 26(2). 679–689. 4 indexed citations
14.
Martínez, Fabio, et al.. (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.
15.
Romo‐Bucheli, David, et al.. (2021). A digital cardiac disease biomarker from a generative progressive cardiac cine-MRI representation. Biomedical Engineering Letters. 12(1). 75–84. 2 indexed citations
16.
Martínez, Fabio, et al.. (2021). How important is motion in sign language translation?. IET Computer Vision. 15(3). 224–234. 4 indexed citations
17.
Pertuz, Said, et al.. (2020). A convolutional oculomotor representation to model parkinsonian fixational patterns from magnified videos. Pattern Analysis and Applications. 24(2). 445–457. 5 indexed citations
18.
Pertuz, Said, et al.. (2020). Multi-modal RGB-D Image Segmentation from Appearance and Geometric Depth Maps. SHILAP Revista de lepidopterología. 23(48). 143–161. 1 indexed citations
19.
Martínez, Fabio, Francisco Javier Gómez, & Eduardo Romero. (2009). ANÁLISIS DE VÍDEO PARA ESTIMACIÓN DEL MOVIMIENTO HUMANO: UNA REVISIÓN. Redalyc (Universidad Autónoma del Estado de México). 17(1). 95–106. 4 indexed citations
20.
Martínez, Fabio. (1988). Fernando Vallejo: El ángel del apocalipsis. Bogotá (Banco de la República). 25(14). 35–41. 1 indexed citations

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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