Benjamín Gutiérrez-Becker
Impact in
-
- Brain Tumor Detection and Classification
Papers in
-
- Medical Image Segmentation Techniques 2
- Advanced Neural Network Applications 1
- Image Processing and 3D Reconstruction 1
- Co-authors
- Nassir Navab (2 shared papers)Diana Mateus (1 shared paper)Jesús Andrés Benavides-Serralde (1 shared paper)Christian Wachinger (1 shared paper)Loïc Peter (1 shared paper)Fernando Arámbula Cosı́o (1 shared paper)Verónica Medina-Bañuelos (1 shared paper)Ignacio Sarasúa (1 shared paper)
- Journals
- Medical Image Analysis (2 papers)Computerized Medical Imaging and Graphics (1 paper)International Journal of Computer Assisted Radiology and Surgery (1 paper)Frontiers in Neuroscience (1 paper)Medical & Biological Engineering & Computing (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Benjamín Gutiérrez-Becker
6 papers receiving 141 citations
Peers
Comparison fields: 5 of 68
- Neurology 21
- Aging 3
- Radiology, Nuclear Medicine and Imaging 37
- Health Informatics 2
- Computer Vision and Pattern Recognition 28
Countries citing papers authored by Benjamín Gutiérrez-Becker
This map shows the geographic impact of Benjamín Gutiérrez-Becker'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 Benjamín Gutiérrez-Becker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamín Gutiérrez-Becker more than expected).
Fields of papers citing papers by Benjamín Gutiérrez-Becker
This network shows the impact of papers produced by Benjamín Gutiérrez-Becker. 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 Benjamín Gutiérrez-Becker. The network helps show where Benjamín Gutiérrez-Becker may publish in the future.
Co-authors
The 25 scholars most cited alongside Benjamín Gutiérrez-Becker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 60 | |
| 2 | 2017 | 28 | |
| 3 | 2013 | 24 | |
| 4 | 2017 | 15 | |
| 5 | 2020 | 11 | |
| 6 | 2024 | 6 |
About Benjamín Gutiérrez-Becker
Benjamín Gutiérrez-Becker is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology and Biomedical Engineering, having authored 6 papers that have together received 144 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Image Segmentation Techniques (2 papers), Medical Imaging and Analysis (2 papers), Advanced Neural Network Applications (1 paper), 3D Shape Modeling and Analysis (1 paper), Image Processing and 3D Reconstruction (1 paper), Neuroinflammation and Neurodegeneration Mechanisms (1 paper) and Brain Tumor Detection and Classification (1 paper). The work is most often cited by research in Neurology (21 citations), Aging (3 citations), Radiology, Nuclear Medicine and Imaging (37 citations), Health Informatics (2 citations) and Computer Vision and Pattern Recognition (28 citations). Benjamín Gutiérrez-Becker has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Nassir Navab, Diana Mateus, Jesús Andrés Benavides-Serralde, Christian Wachinger, Loïc Peter, Fernando Arámbula Cosı́o, Verónica Medina-Bañuelos, Ignacio Sarasúa, Amin Katouzian and Antonella Castellano. Their work appears in journals such as Medical Image Analysis, Computerized Medical Imaging and Graphics, International Journal of Computer Assisted Radiology and Surgery, Frontiers in Neuroscience and Medical & Biological Engineering & Computing.
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.