Sandro De Zanet

631 total citations
20 papers, 210 citations indexed

About

Sandro De Zanet is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sandro De Zanet has authored 20 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 16 papers in Ophthalmology and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sandro De Zanet's work include Retinal Imaging and Analysis (19 papers), Retinal Diseases and Treatments (15 papers) and Retinal and Optic Conditions (7 papers). Sandro De Zanet is often cited by papers focused on Retinal Imaging and Analysis (19 papers), Retinal Diseases and Treatments (15 papers) and Retinal and Optic Conditions (7 papers). Sandro De Zanet collaborates with scholars based in Switzerland, Australia and Spain. Sandro De Zanet's co-authors include Agata Mosinska, Carlos Ciller, Stefanos Apostolopoulos, Raphael Sznitman, Martin S. Zinkernagel, Sebastián Wolf, Irmela Mantel, Marion R. Munk, Thomas Kurmann and Jacopo Guidotti and has published in prestigious journals such as PLoS ONE, Scientific Reports and Ultramicroscopy.

In The Last Decade

Sandro De Zanet

18 papers receiving 209 citations

Peers

Sandro De Zanet
Carlos Ciller Switzerland
Stefanos Apostolopoulos Switzerland
Ariel J. Tyring United States
Nicolaas P. DeRuyter United States
Kaveri A. Thakoor United States
Alisa T. Thavikulwat United States
Gidi Benyamini United States
Hina Raja United States
Abraham Olvera‐Barrios United Kingdom
Naoko Takada Japan
Carlos Ciller Switzerland
Sandro De Zanet
Citations per year, relative to Sandro De Zanet Sandro De Zanet (= 1×) peers Carlos Ciller

Countries citing papers authored by Sandro De Zanet

Since Specialization
Citations

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

Fields of papers citing papers by Sandro De Zanet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sandro De Zanet. 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 Sandro De Zanet. The network helps show where Sandro De Zanet may publish in the future.

Co-authorship network of co-authors of Sandro De Zanet

This figure shows the co-authorship network connecting the top 25 collaborators of Sandro De Zanet. A scholar is included among the top collaborators of Sandro De Zanet 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 Sandro De Zanet. Sandro De Zanet 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.
Wu, Zhichao, et al.. (2025). Loss of OCT Outer Retinal Bands as Potential Clinical Trial Endpoints in Intermediate Age-Related Macular Degeneration. Ophthalmology Science. 5(4). 100769–100769. 2 indexed citations
2.
Mantel, Irmela, Romina Mayra Lasagni Vitar, & Sandro De Zanet. (2025). Modeling pegcetacoplan treatment effect for atrophic age-related macular degeneration with AI-based progression prediction. International Journal of Retina and Vitreous. 11(1). 14–14. 2 indexed citations
3.
4.
González, Rodrigo Abreu, Romina Mayra Lasagni Vitar, Carlos Ciller, et al.. (2025). Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study. BMJ Open Ophthalmology. 10(1). e002109–e002109.
5.
Vitar, Romina Mayra Lasagni, Rodrigo Abreu González, J. Donate-López, et al.. (2023). Development of LuxIA, a Cloud-Based AI Diabetic Retinopathy Screening Tool Using a Single Color Fundus Image. Translational Vision Science & Technology. 12(11). 38–38. 4 indexed citations
6.
7.
Montesel, Andrea, Agata Mosinska, Stefanos Apostolopoulos, et al.. (2022). Automated foveal location detection on spectral-domain optical coherence tomography in geographic atrophy patients. Graefe s Archive for Clinical and Experimental Ophthalmology. 260(7). 2261–2270. 2 indexed citations
8.
Munk, Marion R., Thomas Kurmann, Sandro De Zanet, et al.. (2021). Machine Learning Can Predict Anti–VEGF Treatment Demand in a Treat-and-Extend Regimen for Patients with Neovascular AMD, DME, and RVO Associated Macular Edema. Ophthalmology Retina. 5(7). 604–624. 55 indexed citations
9.
Mosinska, Agata, et al.. (2021). Fully-automated atrophy segmentation in dry age-related macular degeneration in optical coherence tomography. Scientific Reports. 11(1). 21893–21893. 20 indexed citations
10.
Mantel, Irmela, Agata Mosinska, Ciara Bergin, et al.. (2021). Automated Quantification of Pathological Fluids in Neovascular Age-Related Macular Degeneration, and Its Repeatability Using Deep Learning. Translational Vision Science & Technology. 10(4). 17–17. 26 indexed citations
11.
Mosinska, Agata, Andrea Montesel, Stefanos Apostolopoulos, et al.. (2021). Personalized Atrophy Risk Mapping in Age-Related Macular Degeneration. Translational Vision Science & Technology. 10(13). 18–18. 15 indexed citations
12.
Apostolopoulos, Stefanos, Carlos Ciller, Andreas Ebneter, et al.. (2020). Automatically Enhanced OCT Scans of the Retina: A proof of concept study. Scientific Reports. 10(1). 7819–7819. 19 indexed citations
13.
Berger, Lieselotte, Gerd Klose, Sandro De Zanet, et al.. (2020). Comparison of Drusen Volume Assessed by Two Different OCT Devices. Journal of Clinical Medicine. 9(8). 2657–2657. 3 indexed citations
14.
Zanet, Sandro De, Agata Mosinska, Ciara Bergin, et al.. (2020). Automated detection and quantification of pathological fluid in neovascular age-related macular degeneration using a deep learning approach. 61(7). 1655–1655. 5 indexed citations
15.
Vente, Coen de, Carlos Ciller, Sandro De Zanet, et al.. (2020). Estimating Uncertainty of Deep Neural Networks for Age-related Macular Degeneration Grading using Optical Coherence Tomography. 61(7). 1630–1630. 3 indexed citations
16.
Huf, Wolfgang, Karen B. Schaal, Chantal Dysli, et al.. (2019). Comparison of Choroidal Thickness Measurements Using Spectral Domain Optical Coherence Tomography in Six Different Settings and With Customized Automated Segmentation Software. Translational Vision Science & Technology. 8(3). 5–5. 2 indexed citations
17.
Oveisi, Emad, Sandro De Zanet, G. Lucas, et al.. (2017). Stereo-vision three-dimensional reconstruction of curvilinear structures imaged with a TEM. Ultramicroscopy. 184(Pt A). 116–124. 17 indexed citations
18.
Ciller, Carlos, Sandro De Zanet, Konstantinos Kamnitsas, et al.. (2017). Multi-channel MRI segmentation of eye structures and tumors using patient-specific features. PLoS ONE. 12(3). e0173900–e0173900. 10 indexed citations
19.
Zanet, Sandro De, Tobias Rudolph, Rogério Richa, Christoph Tappeiner, & Raphael Sznitman. (2016). Retinal slit lamp video mosaicking. International Journal of Computer Assisted Radiology and Surgery. 11(6). 1035–1041. 7 indexed citations
20.
Dufour, Pascal, Sandro De Zanet, Ute Wolf-Schnurrbusch, & Jens Kowal. (2012). Classification of drusen positions in optical coherence tomography data from patients with age-related macular degeneration. 2067–2070. 4 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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