Alessandro Sciarra

689 total citations
16 papers, 446 citations indexed

About

Alessandro Sciarra is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Alessandro Sciarra has authored 16 papers receiving a total of 446 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Cognitive Neuroscience. Recurrent topics in Alessandro Sciarra's work include Advanced MRI Techniques and Applications (11 papers), Medical Imaging Techniques and Applications (7 papers) and Advanced Neuroimaging Techniques and Applications (3 papers). Alessandro Sciarra is often cited by papers focused on Advanced MRI Techniques and Applications (11 papers), Medical Imaging Techniques and Applications (7 papers) and Advanced Neuroimaging Techniques and Applications (3 papers). Alessandro Sciarra collaborates with scholars based in Germany, Italy and United Kingdom. Alessandro Sciarra's co-authors include Oliver Speck, Falk Lüsebrink, Renat Yakupov, Hendrik Mattern, Frank Godenschweger, Daniel Stucht, Uten Yarach, Ana María, Stefano Salciccia and Alessandro Gentilucci and has published in prestigious journals such as The Journal of Urology, Magnetic Resonance in Medicine and Physics in Medicine and Biology.

In The Last Decade

Alessandro Sciarra

16 papers receiving 440 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alessandro Sciarra Germany 9 315 130 74 39 34 16 446
Michael N. Hoff United States 10 400 1.3× 76 0.6× 40 0.5× 13 0.3× 29 0.9× 25 523
Olutayo I. Olubiyi United States 14 341 1.1× 86 0.7× 67 0.9× 23 0.6× 21 0.6× 21 650
Jae‐Yong Han South Korea 12 224 0.7× 59 0.5× 60 0.8× 10 0.3× 17 0.5× 16 402
Yingjian Yu United States 8 383 1.2× 51 0.4× 45 0.6× 48 1.2× 10 0.3× 16 604
Yihao Guo China 12 345 1.1× 34 0.3× 61 0.8× 15 0.4× 53 1.6× 43 512
Steven H. Baete United States 14 591 1.9× 65 0.5× 73 1.0× 14 0.4× 18 0.5× 35 755
M. Ethan MacDonald Canada 12 250 0.8× 77 0.6× 121 1.6× 33 0.8× 9 0.3× 38 514
Gary Gillan United States 8 298 0.9× 125 1.0× 53 0.7× 26 0.7× 17 0.5× 9 501
Tom Hilbert Switzerland 15 554 1.8× 63 0.5× 79 1.1× 9 0.2× 55 1.6× 66 739
Jonathan Goodwin Japan 12 269 0.9× 67 0.5× 92 1.2× 7 0.2× 10 0.3× 22 374

Countries citing papers authored by Alessandro Sciarra

Since Specialization
Citations

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

Fields of papers citing papers by Alessandro Sciarra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alessandro Sciarra

This figure shows the co-authorship network connecting the top 25 collaborators of Alessandro Sciarra. A scholar is included among the top collaborators of Alessandro Sciarra 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 Alessandro Sciarra. Alessandro Sciarra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Chatterjee, Soumick, Alessandro Sciarra, Pavan Tummala, et al.. (2024). Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution. Journal of Imaging. 10(9). 207–207. 2 indexed citations
2.
Chatterjee, Soumick, et al.. (2023). Uncertainty quantification for ground-truth free evaluation of deep learning reconstructions. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 1 indexed citations
3.
Placidi, Giuseppe, Luigi Cinque, Michele Nappi, et al.. (2022). Star-Net: a Multi-Branch Convolutional Network for Multiple Source Image Segmentation. 127–134. 1 indexed citations
4.
Iamshchinina, Polina, Daniel Kaiser, Renat Yakupov, et al.. (2021). Perceived and mentally rotated contents are differentially represented in cortical depth of V1. Communications Biology. 4(1). 1069–1069. 19 indexed citations
5.
Chatterjee, Soumick, et al.. (2021). ShuffleUNet: Super resolution of diffusion-weighted MRIs using deep learning. 2021 29th European Signal Processing Conference (EUSIPCO). 940–944. 16 indexed citations
6.
Sciarra, Alessandro, Hendrik Mattern, Renat Yakupov, et al.. (2021). Quantitative evaluation of prospective motion correction in healthy subjects at 7T MRI. Magnetic Resonance in Medicine. 87(2). 646–657. 3 indexed citations
7.
Iamshchinina, Polina, Daniel Kaiser, Renat Yakupov, et al.. (2020). Perceived and mentally rotated contents are differentially represented in cortical layers of V1. Journal of Vision. 20(11). 766–766. 1 indexed citations
8.
Mattern, Hendrik, Alessandro Sciarra, Falk Lüsebrink, Julio Acosta‐Cabronero, & Oliver Speck. (2018). Prospective motion correction improves high‐resolution quantitative susceptibility mapping at 7T. Magnetic Resonance in Medicine. 81(3). 1605–1619. 30 indexed citations
9.
Lüsebrink, Falk, Alessandro Sciarra, Hendrik Mattern, Renat Yakupov, & Oliver Speck. (2017). T1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 μm. Scientific Data. 4(1). 170032–170032. 56 indexed citations
10.
Yarach, Uten, Myung‐Ho In, Itthi Chatnuntawech, et al.. (2017). Model‐based iterative reconstruction for single‐shot EPI at 7T. Magnetic Resonance in Medicine. 78(6). 2250–2264. 12 indexed citations
11.
Mattern, Hendrik, Alessandro Sciarra, Frank Godenschweger, et al.. (2017). Prospective motion correction enables highest resolution time‐of‐flight angiography at 7T. Magnetic Resonance in Medicine. 80(1). 248–258. 36 indexed citations
12.
Godenschweger, Frank, Daniel Stucht, Uten Yarach, et al.. (2016). Motion correction in MRI of the brain. Physics in Medicine and Biology. 61(5). R32–R56. 138 indexed citations
13.
Florio, Tiziana M., et al.. (2013). Switching ability of over trained movements in a Parkinson’s disease rat model. Behavioural Brain Research. 250. 326–333. 9 indexed citations
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16.
Sciarra, Alessandro, Valeria Panebianco, Stefano Salciccia, et al.. (2008). ROLE OF DYNAMIC CONTRAST ENHANCED MAGNETIC RESONANCE (MR) IMAGING AND PROTON MR SPECTROSCOPIC IMAGING IN THE DETECTION OF LOCAL RECURRENCE AFTER RADICAL PROSTATECTOMY FOR PROSTATE CANCER. The Journal of Urology. 179(4S). 642–642. 120 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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