G. van de Wouwer
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging
- Media Technology top 10%
- Co-authors
- Paul ScheundersD. Van DyckStefan LivensBarbara WeynEric Van MarckWillem JacobWalter BogaertsSamir Kumar‐Singh
- Topics
- Medical Image Segmentation Techniques (6 papers)Image Retrieval and Classification Techniques (5 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)
- Partner nations
- BelgiumUnited States
In The Last Decade
G. van de Wouwer
15 papers receiving 281 citations
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 177
- Artificial Intelligence 109
- Molecular Biology 45
- Radiology, Nuclear Medicine and Imaging 45
- Media Technology 44
Countries citing papers authored by G. van de Wouwer
This map shows the geographic impact of G. van de Wouwer'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 G. van de Wouwer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. van de Wouwer more than expected).
Fields of papers citing papers by G. van de Wouwer
This network shows the impact of papers produced by G. van de Wouwer. 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 G. van de Wouwer. The network helps show where G. van de Wouwer may publish in the future.
Co-authorship network of co-authors of G. van de Wouwer
This figure shows the co-authorship network connecting the top 25 collaborators of G. van de Wouwer. A scholar is included among the top collaborators of G. van de Wouwer 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 G. van de Wouwer. G. van de Wouwer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 21 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | Validation of nuclear texture, density, morphometry and tissue syntactic structure analysis as prognosticators of cervical carcinoma. | 12 |
| 7 | Wavelet-based texture classification | 4 |
| 8 | 33 | |
| 9 | 20 | |
| 10 | 90 | |
| 11 | 61 | |
| 12 | Wavelets for texture analysis: an overview | 2 |
| 13 | Rotation-invariant texture segmentation using continuous wavelets | 1 |
| 14 | 2 | |
| 15 | 41 |
About G. van de Wouwer
G. van de Wouwer is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 302 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (6 papers), Image Retrieval and Classification Techniques (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (177 citations), Biophysics (38 citations) and Media Technology (44 citations). G. van de Wouwer has collaborated with scholars based in Belgium and United States. Frequent co-authors include Paul Scheunders, D. Van Dyck, Stefan Livens, Barbara Weyn, Eric Van Marck, Willem Jacob, Walter Bogaerts, Samir Kumar‐Singh, Annelieke K. Peters and Philippe Vanparys. Their work appears in journals such as Pattern Recognition, The Journal of Pathology and Journal of Microscopy.
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.