Daniele Perrone
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Media Technology top 2%
- Cognitive Neuroscience
- Pediatrics, Perinatology and Child Health
- Co-authors
- Paolo FavaroJan AeltermanWilfried PhilipsAlexander LeemansBen JeurissenTimo RoineJan SijbersAleksandra Pižurica
- Topics
- Advanced Neuroimaging Techniques and Applications (6 papers)Advanced MRI Techniques and Applications (5 papers)Advanced Image Processing Techniques (5 papers)
- Cited by
- Media TechnologyComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Partner nations
- NetherlandsSwitzerlandBelgium
In The Last Decade
Daniele Perrone
12 papers receiving 505 citations
Peers
Comparison fields: 5 of 64
- Computer Vision and Pattern Recognition 279
- Radiology, Nuclear Medicine and Imaging 202
- Media Technology 189
- Cognitive Neuroscience 78
- Pediatrics, Perinatology and Child Health 50
Countries citing papers authored by Daniele Perrone
This map shows the geographic impact of Daniele Perrone'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 Daniele Perrone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniele Perrone more than expected).
Fields of papers citing papers by Daniele Perrone
This network shows the impact of papers produced by Daniele Perrone. 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 Daniele Perrone. The network helps show where Daniele Perrone may publish in the future.
Co-authorship network of co-authors of Daniele Perrone
This figure shows the co-authorship network connecting the top 25 collaborators of Daniele Perrone. A scholar is included among the top collaborators of Daniele Perrone 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 Daniele Perrone. Daniele Perrone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 39 | |
| 2 | 6 | |
| 3 | 5 | |
| 4 | 86 | |
| 5 | 29 | |
| 6 | 35 | |
| 7 | 67 | |
| 8 | 52 | |
| 9 | 185 | |
| 10 | 6 | |
| 11 | Correction of Gibbs ringing in diffusion MRI data using total variation regularization | 2 |
| 12 | Gibbs artifact suppression for DT-MRI data | 1 |
About Daniele Perrone
Daniele Perrone is a scholar working on Media Technology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 513 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (6 papers), Advanced MRI Techniques and Applications (5 papers) and Advanced Image Processing Techniques (5 papers). The work is most often cited by research in Media Technology (189 citations), Computer Vision and Pattern Recognition (279 citations) and Radiology, Nuclear Medicine and Imaging (202 citations). Daniele Perrone has collaborated with scholars based in Netherlands, Switzerland and Belgium. Frequent co-authors include Paolo Favaro, Jan Aelterman, Wilfried Philips, Alexander Leemans, Ben Jeurissen, Timo Roine, Jan Sijbers, Aleksandra Pižurica, Renè Vidal and Avinash Ravichandran. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.
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.