Enea Poletti

646 total citations
25 papers, 462 citations indexed

About

Enea Poletti is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Enea Poletti has authored 25 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Ophthalmology and 7 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Enea Poletti's work include Retinal Imaging and Analysis (9 papers), Corneal surgery and disorders (8 papers) and Ocular Surface and Contact Lens (6 papers). Enea Poletti is often cited by papers focused on Retinal Imaging and Analysis (9 papers), Corneal surgery and disorders (8 papers) and Ocular Surface and Contact Lens (6 papers). Enea Poletti collaborates with scholars based in Italy, United States and Germany. Enea Poletti's co-authors include Alfredo Ruggeri, Enrico Grisan, Neil Lagali, Tor Paaske Utheim, Pedro Guimarães, Christopher Tomelleri, Oliver Stachs, Lara Tramontan, Paolo Lanzetta and Rudolf Guthoff and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Biomedical Engineering and Investigative Ophthalmology & Visual Science.

In The Last Decade

Enea Poletti

25 papers receiving 437 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Enea Poletti Italy 12 234 177 176 114 104 25 462
Alina V. Dumitrescu United States 11 317 1.4× 344 1.9× 17 0.1× 76 0.7× 204 2.0× 35 622
Bojie Hu China 14 252 1.1× 295 1.7× 15 0.1× 11 0.1× 84 0.8× 44 619
Ariane Machado‐Lima Brazil 11 34 0.1× 11 0.1× 67 0.4× 44 0.4× 140 1.3× 39 422
Ce Zheng China 18 1.1k 4.7× 1.2k 6.7× 123 0.7× 12 0.1× 45 0.4× 49 1.3k
David Parry United Kingdom 11 197 0.8× 189 1.1× 23 0.1× 52 0.5× 33 0.3× 18 355
Subbaiah Ramasamy Krishnadas India 14 449 1.9× 550 3.1× 18 0.1× 24 0.2× 117 1.1× 37 665
Di Gong China 9 195 0.8× 206 1.2× 10 0.1× 17 0.1× 39 0.4× 25 331
Eduardo Martínez-Enríquez Spain 16 404 1.7× 321 1.8× 68 0.4× 5 0.0× 38 0.4× 49 653
Huiling Hu China 10 35 0.1× 36 0.2× 39 0.2× 22 0.2× 83 0.8× 32 329

Countries citing papers authored by Enea Poletti

Since Specialization
Citations

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

Fields of papers citing papers by Enea Poletti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Enea Poletti

This figure shows the co-authorship network connecting the top 25 collaborators of Enea Poletti. A scholar is included among the top collaborators of Enea Poletti 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 Enea Poletti. Enea Poletti 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.
Wintergerst, Maximilian W. M., Moritz Berger, Chantal Dysli, et al.. (2022). Spectrally resolved autofluorescence imaging in posterior uveitis. Scientific Reports. 12(1). 14337–14337. 5 indexed citations
2.
Sarao, Valentina, et al.. (2019). A comparison between a white LED confocal imaging system and a conventional flash fundus camera using chromaticity analysis. BMC Ophthalmology. 19(1). 231–231. 23 indexed citations
3.
Poletti, Enea, et al.. (2015). Age-Related Changes in Murine Corneal Nerves. Current Eye Research. 41(8). 1021–1028. 17 indexed citations
4.
Poletti, Enea, et al.. (2015). Corneal Nerve Regeneration After Collagen Cross-Linking Treatment of Keratoconus. JAMA Ophthalmology. 134(1). 70–70. 36 indexed citations
5.
Guimarães, Pedro, et al.. (2014). A fully-automatic fast segmentation of the sub-basal layer nerves in corneal images. PubMed. 2014. 5422–5425. 8 indexed citations
6.
Guimarães, Pedro, et al.. (2014). Automatic detection of microdots in the stromal layer of corneal images. PubMed. 24. 210–213. 2 indexed citations
7.
Poletti, Enea & Enrico Grisan. (2014). A boosted optimal linear learner for retinal vessel segmentation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9035. 903530–903530. 1 indexed citations
8.
Poletti, Enea, et al.. (2013). Super-image mosaic of infant retinal fundus: Selection and registration of the best-quality frames from videos. PubMed. 2013. 5883–5886. 4 indexed citations
9.
Poletti, Enea, et al.. (2013). Standardized Baseline Human Corneal Subbasal Nerve Density for Clinical Investigations With Laser-Scanning in Vivo Confocal Microscopy. Investigative Ophthalmology & Visual Science. 54(10). 7091–7091. 83 indexed citations
10.
Poletti, Enea, E. Veronese, Massimiliano Calabrese, Alessandra Bertoldo, & Enrico Grisan. (2012). Supervised classification of brain tissues through local multi-scale texture analysis by coupling DIR and FLAIR MR sequences. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8314. 83142T–83142T. 2 indexed citations
11.
Poletti, Enea, et al.. (2012). A review of thresholding strategies applied to human chromosome segmentation. Computer Methods and Programs in Biomedicine. 108(2). 679–688. 48 indexed citations
12.
Poletti, Enea, Enrico Grisan, & Alfredo Ruggeri. (2012). Image-level tortuosity estimation in wide-field retinal images from infants with Retinopathy of Prematurity. PubMed. 2012. 4958–4961. 12 indexed citations
13.
Poletti, Enea, Alfredo Ruggeri, & Enrico Grisan. (2011). An improved classification scheme for chromosomes with missing data. PubMed. 2011. 5072–5075. 8 indexed citations
14.
Poletti, Enea, et al.. (2011). Automatic vessel segmentation in wide-field retina images of infants with Retinopathy of Prematurity. PubMed. 44. 3954–3957. 9 indexed citations
15.
Ruggeri, Alfredo, et al.. (2011). From laboratory to clinic: The development of web-based tools for the estimation of retinal diagnostic parameters. PubMed. 33. 3379–3382. 5 indexed citations
16.
Poletti, Enea, Enrico Grisan, & Alfredo Ruggeri. (2011). A modular framework for the automatic classification of chromosomes in Q-band images. Computer Methods and Programs in Biomedicine. 105(2). 120–130. 25 indexed citations
17.
Tramontan, Lara, et al.. (2010). A Web-Based System for the Quantitative and Reproducible Assessment of Clinical Indexes From the Retinal Vasculature. IEEE Transactions on Biomedical Engineering. 58(3). 818–821. 9 indexed citations
18.
Grisan, Enrico, Enea Poletti, & Alfredo Ruggeri. (2009). Automatic Segmentation and Disentangling of Chromosomes in Q-Band Prometaphase Images. IEEE Transactions on Information Technology in Biomedicine. 13(4). 575–581. 59 indexed citations
19.
Poletti, Enea, Enrico Grisan, & Alfredo Ruggeri. (2008). Automatic classification of chromosomes in Q-band images. PubMed. 2008. 1911–1914. 25 indexed citations
20.
Grisan, Enrico, Enea Poletti, Christopher Tomelleri, & Alfredo Ruggeri. (2007). Automatic segmentation of chromosomes in Q-band images. Conference proceedings. 2007. 5513–5516. 19 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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