Daniel Racoceanu
Impact in
- Biophysics top 0.5%
- Cell Image Analysis Techniques
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- Digital Imaging for Blood Diseases
- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Image Retrieval and Classification Techniques
Papers in
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- AI in cancer detection 38
- Neural Networks and Applications 10
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- Image Retrieval and Classification Techniques 16
- Medical Image Segmentation Techniques 12
- Digital Imaging for Blood Diseases 11
- Co-authors
- Humayun Irshad (6 shared papers)Ludovic Roux (9 shared papers)Antoine Veillard (10 shared papers)Noureddine Zerhouni (11 shared papers)Ryad Zemouri (6 shared papers)Chandan Chakraborty (1 shared paper)Nicolas Loménie (8 shared papers)Monjoy Saha (1 shared paper)
In The Last Decade
Daniel Racoceanu
90 papers receiving 2.7k citations
Daniel Racoceanu's Hit Papers
Peers
Comparison fields: 5 of 162
- Biophysics 518
- Computer Vision and Pattern Recognition 1.3k
- Artificial Intelligence 1.8k
- Radiology, Nuclear Medicine and Imaging 1.0k
- Health Informatics 49
Countries citing papers authored by Daniel Racoceanu
This map shows the geographic impact of Daniel Racoceanu'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 Daniel Racoceanu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Racoceanu more than expected).
Fields of papers citing papers by Daniel Racoceanu
This network shows the impact of papers produced by Daniel Racoceanu. 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 Daniel Racoceanu. The network helps show where Daniel Racoceanu may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Racoceanu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Gland segmentation in colon histology images: The glas challenge contest Hit paper breakdown → | 2016 | 570 |
| 2 | Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review—Current Status and Future Potential Hit paper breakdown → | 2014 | 458 |
| 3 | 2013 | 217 | |
| 4 | 2017 | 147 | |
| 5 | 2019 | 130 | |
| 6 | 2020 | 127 | |
| 7 | 2020 | 91 | |
| 8 | 2003 | 87 | |
| 9 | 2010 | 83 | |
| 10 | 2013 | 82 | |
| 11 | 2008 | 70 | |
| 12 | 2021 | 69 | |
| 13 | 2010 | 46 | |
| 14 | 2019 | 44 | |
| 15 | Nuclear pleomorphism scoring by selective cell nuclei detection | 2009 | 35 |
| 16 | 2014 | 33 | |
| 17 | 2012 | 31 | |
| 18 | 2012 | 26 | |
| 19 | 2013 | 23 | |
| 20 | 2020 | 22 |
About Daniel Racoceanu
Daniel Racoceanu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 97 papers that have together received 2.8k indexed citations. Recurring topics across this work include AI in cancer detection (38 papers), Cell Image Analysis Techniques (23 papers), Image Retrieval and Classification Techniques (16 papers), Radiomics and Machine Learning in Medical Imaging (15 papers), Medical Image Segmentation Techniques (12 papers), Biomedical Text Mining and Ontologies (12 papers), Digital Imaging for Blood Diseases (11 papers) and Neural Networks and Applications (10 papers). The work is most often cited by research in Biophysics (518 citations), Computer Vision and Pattern Recognition (1.3k citations), Artificial Intelligence (1.8k citations), Radiology, Nuclear Medicine and Imaging (1.0k citations) and Health Informatics (49 citations). Daniel Racoceanu has collaborated with scholars based in France, Singapore and Peru. Frequent co-authors include Humayun Irshad, Ludovic Roux, Antoine Veillard, Noureddine Zerhouni, Ryad Zemouri, Chandan Chakraborty, Nicolas Loménie, Monjoy Saha, Bassem Ben Cheikh and Diana Mateus. Their work appears in journals such as Computerized Medical Imaging and Graphics, IEEE Transactions on Biomedical Engineering, Journal of Pathology Informatics, Gerontology and Frontiers in Bioengineering and Biotechnology.
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.