Laurent Massoptier
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Neurology top 10%
- Co-authors
- Sergio CasciaroJosé DolzMaximilien VermandelRoberto FranchiniFrancesco ConversanoAntonio MalvasıNicolas ReynsA. Lay-Ekuakille
- Topics
- Medical Image Segmentation Techniques (15 papers)Radiomics and Machine Learning in Medical Imaging (9 papers)Brain Tumor Detection and Classification (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingHealth Informatics
In The Last Decade
Laurent Massoptier
22 papers receiving 523 citations
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 263
- Radiology, Nuclear Medicine and Imaging 252
- Artificial Intelligence 142
- Biomedical Engineering 128
- Neurology 74
Countries citing papers authored by Laurent Massoptier
This map shows the geographic impact of Laurent Massoptier'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 Laurent Massoptier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laurent Massoptier more than expected).
Fields of papers citing papers by Laurent Massoptier
This network shows the impact of papers produced by Laurent Massoptier. 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 Laurent Massoptier. The network helps show where Laurent Massoptier may publish in the future.
Co-authorship network of co-authors of Laurent Massoptier
This figure shows the co-authorship network connecting the top 25 collaborators of Laurent Massoptier. A scholar is included among the top collaborators of Laurent Massoptier 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 Laurent Massoptier. Laurent Massoptier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 19 | |
| 2 | 1 | |
| 3 | 35 | |
| 4 | 26 | |
| 5 | 30 | |
| 6 | 37 | |
| 7 | 22 | |
| 8 | 10 | |
| 9 | Segmentation algorithms of subcortical brain structures on MRI:a review | 1 |
| 10 | 3 | |
| 11 | 0 | |
| 12 | 48 | |
| 13 | 42 | |
| 14 | 2 | |
| 15 | 10 | |
| 16 | 48 | |
| 17 | 5 | |
| 18 | 128 | |
| 19 | 8 | |
| 20 | 58 |
About Laurent Massoptier
Laurent Massoptier is a scholar working on Computer Vision and Pattern Recognition, Neurology and Radiology, Nuclear Medicine and Imaging, having authored 23 papers that have together received 543 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (15 papers), Radiomics and Machine Learning in Medical Imaging (9 papers) and Brain Tumor Detection and Classification (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (263 citations), Radiology, Nuclear Medicine and Imaging (252 citations) and Health Informatics (14 citations). Laurent Massoptier has collaborated with scholars based in Italy, France and Germany. Frequent co-authors include Sergio Casciaro, José Dolz, Maximilien Vermandel, Roberto Franchini, Francesco Conversano, Antonio Malvası, Nicolas Reyns, A. Lay-Ekuakille, Ursula Nestle and Alfonso Maffezzoli. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Medical Physics and Radiotherapy and Oncology.
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.