Arnaldo Mayer

953 total citations
45 papers, 584 citations indexed

About

Arnaldo Mayer is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Arnaldo Mayer has authored 45 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Radiology, Nuclear Medicine and Imaging, 20 papers in Computer Vision and Pattern Recognition and 10 papers in Biomedical Engineering. Recurrent topics in Arnaldo Mayer's work include Advanced Neuroimaging Techniques and Applications (13 papers), Medical Image Segmentation Techniques (12 papers) and Advanced MRI Techniques and Applications (10 papers). Arnaldo Mayer is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (13 papers), Medical Image Segmentation Techniques (12 papers) and Advanced MRI Techniques and Applications (10 papers). Arnaldo Mayer collaborates with scholars based in Israel, United States and Canada. Arnaldo Mayer's co-authors include Hayit Greenspan, Jacob Goldberger, Eli Konen, Nahum Kiryati, Netta Levin, Atira Bick, Edith M. Marom, Miri Sklair‐Levy, Orith Portnoy and Eldad Katorza and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Medical Imaging.

In The Last Decade

Arnaldo Mayer

40 papers receiving 559 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arnaldo Mayer Israel 13 256 222 107 100 67 45 584
Dzhoshkun I. Shakir United Kingdom 9 160 0.6× 221 1.0× 131 1.2× 105 1.1× 49 0.7× 22 532
Tassilo Klein Germany 12 269 1.1× 214 1.0× 160 1.5× 125 1.3× 30 0.4× 28 632
Seyed Sadegh Mohseni Salehi United States 11 249 1.0× 267 1.2× 173 1.6× 83 0.8× 126 1.9× 15 628
Haseeb Hassan China 13 151 0.6× 166 0.7× 93 0.9× 58 0.6× 37 0.6× 45 514
Adriënne M. Mendrik Netherlands 12 172 0.7× 263 1.2× 89 0.8× 163 1.6× 17 0.3× 23 625
Žiga Špiclin Slovenia 14 298 1.2× 259 1.2× 63 0.6× 134 1.3× 18 0.3× 53 714
Alessandro Crimi Switzerland 13 196 0.8× 234 1.1× 98 0.9× 106 1.1× 38 0.6× 48 623
Gerard Sanromà Spain 14 274 1.1× 109 0.5× 117 1.1× 35 0.3× 111 1.7× 28 510
Dexing Kong China 14 133 0.5× 381 1.7× 211 2.0× 82 0.8× 21 0.3× 54 664
Tom Brosch Germany 10 278 1.1× 288 1.3× 215 2.0× 115 1.1× 16 0.2× 20 699

Countries citing papers authored by Arnaldo Mayer

Since Specialization
Citations

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

Fields of papers citing papers by Arnaldo Mayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arnaldo Mayer

This figure shows the co-authorship network connecting the top 25 collaborators of Arnaldo Mayer. A scholar is included among the top collaborators of Arnaldo Mayer 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 Arnaldo Mayer. Arnaldo Mayer 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.
Mayer, Arnaldo, et al.. (2024). Memory Tract Sparing Using Diffusion Tensor Imaging in Radiation Planning of Primary Brain Tumors. Practical Radiation Oncology. 15(1). e3–e9.
2.
3.
Fried, Shalev, et al.. (2022). Volumetric Brain MRI Study in Fetuses with Intrauterine Growth Restriction Using a Semiautomated Method. American Journal of Neuroradiology. 43(11). 1674–1679. 6 indexed citations
4.
Shemesh, Joseph, et al.. (2022). A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation. Clinical Radiology. 77(7). e509–e517. 8 indexed citations
5.
Wolf, Michael S., et al.. (2021). Anisotropic neural deblurring for MRI acceleration. International Journal of Computer Assisted Radiology and Surgery. 17(2). 315–327. 3 indexed citations
6.
Fried, Shalev, et al.. (2021). Correlation between 2D and 3D Fetal Brain MRI Biometry and Neurodevelopmental Outcomes in Fetuses with Suspected Microcephaly and Macrocephaly. American Journal of Neuroradiology. 42(10). 1878–1883. 2 indexed citations
7.
Fried, Shalev, et al.. (2020). Fetal Brain Biometry: Is there an Agreement among Ultrasound, MRI and the Measurements at Birth?. European Journal of Radiology. 133. 109369–109369. 6 indexed citations
8.
Tsarfaty, Galia, et al.. (2019). Neural Segmentation of Seeding ROIs (sROIs) for Pre-Surgical Brain Tractography. IEEE Transactions on Medical Imaging. 39(5). 1655–1667. 6 indexed citations
9.
Katorza, Eldad, et al.. (2019). Volumetric MRI Study of the Brain in Fetuses with Intrauterine Cytomegalovirus Infection and Its Correlation to Neurodevelopmental Outcome. American Journal of Neuroradiology. 40(2). 353–358. 9 indexed citations
10.
Joskowicz, Leo, et al.. (2019). Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings. Medical Image Analysis. 57. 165–175. 23 indexed citations
11.
Klang, Eyal, et al.. (2018). Fully automatic detection of renal cysts in abdominal CT scans. International Journal of Computer Assisted Radiology and Surgery. 13(7). 957–966. 24 indexed citations
12.
Kiryati, Nahum, et al.. (2018). Classification of contrast-enhanced spectral mammography (CESM) images. International Journal of Computer Assisted Radiology and Surgery. 14(2). 249–257. 43 indexed citations
13.
Green, Michael, Edith M. Marom, Eli Konen, Nahum Kiryati, & Arnaldo Mayer. (2018). 3-D Neural denoising for low-dose Coronary CT Angiography (CCTA). Computerized Medical Imaging and Graphics. 70. 185–191. 15 indexed citations
14.
Hoffman, Chen, et al.. (2017). Volume of Structures in the Fetal Brain Measured with a New Semiautomated Method. American Journal of Neuroradiology. 38(11). 2193–2198. 18 indexed citations
15.
Green, Michael, Edith M. Marom, Eli Konen, Nahum Kiryati, & Arnaldo Mayer. (2017). Patient-specific image denoising for ultra-low-dose CT-guided lung biopsies. International Journal of Computer Assisted Radiology and Surgery. 12(12). 2145–2155. 4 indexed citations
16.
Bick, Atira, Arnaldo Mayer, & Netta Levin. (2011). From research to clinical practice: Implementation of functional magnetic imaging and white matter tractography in the clinical environment. Journal of the Neurological Sciences. 312(1-2). 158–165. 25 indexed citations
17.
Mayer, Arnaldo, et al.. (2010). A Supervised Framework for the Registration and Segmentation of White Matter Fiber Tracts. IEEE Transactions on Medical Imaging. 30(1). 131–145. 19 indexed citations
18.
Mayer, Arnaldo, et al.. (2009). Co-registration of White Matter Tractographies by Adaptive-Mean-Shift and Gaussian Mixture Modeling. IEEE Transactions on Medical Imaging. 29(1). 132–145. 24 indexed citations
19.
Mayer, Arnaldo, et al.. (2009). An Adaptive Mean-Shift Framework for MRI Brain Segmentation. IEEE Transactions on Medical Imaging. 28(8). 1238–1250. 124 indexed citations
20.
Greenspan, Hayit, Jacob Goldberger, & Arnaldo Mayer. (2004). Probabilistic space-time video modeling via piecewise gmm. IEEE Transactions on Pattern Analysis and Machine Intelligence. 26(3). 384–396. 96 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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