Marcela Morvidone
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Applied Mathematics top 10%
- Signal Processing
- Co-authors
- Maï K. NguyenHabib ZaidiThérèse TruongLaurent JacquesI. BogdanovaPierre VandergheynstBob L. SturmLaurent Daudet
- Topics
- Medical Imaging Techniques and Applications (10 papers)Advanced X-ray and CT Imaging (9 papers)Image and Signal Denoising Methods (5 papers)
- Cited by
- Applied MathematicsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Partner nations
- ArgentinaFranceSwitzerland
In The Last Decade
Marcela Morvidone
20 papers receiving 219 citations
Peers
Comparison fields: 5 of 53
- Radiology, Nuclear Medicine and Imaging 100
- Computer Vision and Pattern Recognition 79
- Biomedical Engineering 72
- Applied Mathematics 46
- Signal Processing 39
Countries citing papers authored by Marcela Morvidone
This map shows the geographic impact of Marcela Morvidone'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 Marcela Morvidone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcela Morvidone more than expected).
Fields of papers citing papers by Marcela Morvidone
This network shows the impact of papers produced by Marcela Morvidone. 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 Marcela Morvidone. The network helps show where Marcela Morvidone may publish in the future.
Co-authorship network of co-authors of Marcela Morvidone
This figure shows the co-authorship network connecting the top 25 collaborators of Marcela Morvidone. A scholar is included among the top collaborators of Marcela Morvidone 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 Marcela Morvidone. Marcela Morvidone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 7 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 12 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 21 | |
| 11 | Musical instrument identification using multiscale Mel-frequency cepstral coefficients | 18 |
| 12 | 53 | |
| 13 | 11 | |
| 14 | 58 | |
| 15 | 10 | |
| 16 | 3 | |
| 17 | Stereographic Frames of Wavelets on the Sphere | 1 |
| 18 | Weighted BMO spaces and the Hilbert transform | 6 |
| 19 | 1 | |
| 20 | 13 |
About Marcela Morvidone
Marcela Morvidone is a scholar working on Applied Mathematics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 235 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (10 papers), Advanced X-ray and CT Imaging (9 papers) and Image and Signal Denoising Methods (5 papers). The work is most often cited by research in Applied Mathematics (46 citations), Radiology, Nuclear Medicine and Imaging (100 citations) and Computer Vision and Pattern Recognition (79 citations). Marcela Morvidone has collaborated with scholars based in Argentina, France and Switzerland. Frequent co-authors include Maï K. Nguyen, Habib Zaidi, Thérèse Truong, Laurent Jacques, I. Bogdanova, Pierre Vandergheynst, Bob L. Sturm, Laurent Daudet, Bruno Torrésani and T. T. Truong. Their work appears in journals such as Mechanical Systems and Signal Processing, Pattern Recognition Letters and Inverse Problems.
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.