Benoît Naegel

900 total citations
35 papers, 381 citations indexed

About

Benoît Naegel is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Benoît Naegel has authored 35 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 7 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Artificial Intelligence. Recurrent topics in Benoît Naegel's work include Medical Image Segmentation Techniques (17 papers), Image Retrieval and Classification Techniques (13 papers) and Digital Image Processing Techniques (8 papers). Benoît Naegel is often cited by papers focused on Medical Image Segmentation Techniques (17 papers), Image Retrieval and Classification Techniques (13 papers) and Digital Image Processing Techniques (8 papers). Benoît Naegel collaborates with scholars based in France, Switzerland and Germany. Benoît Naegel's co-authors include Nicolas Passat, Christian Ronse, Laurent Wendling, Hugues Talbot, Camille Kurtz, Philippe Bachellier, Pietro Addeo, Vincent Noblet, Olena Tankyevych and J. Baruthio and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Benoît Naegel

33 papers receiving 372 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Benoît Naegel France 13 244 74 59 45 45 35 381
Yung-Nien Sun Taiwan 12 195 0.8× 68 0.9× 41 0.7× 98 2.2× 45 1.0× 38 411
Xuehu Wang China 9 169 0.7× 88 1.2× 97 1.6× 48 1.1× 52 1.2× 22 332
Lars Aurdal Norway 9 103 0.4× 39 0.5× 58 1.0× 46 1.0× 57 1.3× 23 332
Bruno M. Carvalho Brazil 9 214 0.9× 143 1.9× 37 0.6× 23 0.5× 80 1.8× 45 486
Shuqian Luo China 12 201 0.8× 289 3.9× 29 0.5× 27 0.6× 136 3.0× 42 499
Tianyu Shi China 9 168 0.7× 207 2.8× 17 0.3× 15 0.3× 47 1.0× 16 405
Changfa Shi China 8 157 0.6× 145 2.0× 17 0.3× 11 0.2× 56 1.2× 15 298
Heran Yang China 11 121 0.5× 96 1.3× 11 0.2× 21 0.5× 109 2.4× 32 398

Countries citing papers authored by Benoît Naegel

Since Specialization
Citations

This map shows the geographic impact of Benoît Naegel'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 Benoît Naegel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benoît Naegel more than expected).

Fields of papers citing papers by Benoît Naegel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benoît Naegel. 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 Benoît Naegel. The network helps show where Benoît Naegel may publish in the future.

Co-authorship network of co-authors of Benoît Naegel

This figure shows the co-authorship network connecting the top 25 collaborators of Benoît Naegel. A scholar is included among the top collaborators of Benoît Naegel 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 Benoît Naegel. Benoît Naegel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Naegel, Benoît, et al.. (2025). DeepSCEM: A User‐Friendly Solution for Deep Learning‐Based Image Segmentation in Cellular Electron Microscopy. Biology of the Cell. 117(9). e70032–e70032. 1 indexed citations
2.
Schultz, Patrick, et al.. (2023). Fast and Interpretable Unsupervised Domain Adaptation for FIB-SEM Cell Segmentation. SPIRE - Sciences Po Institutional REpository. 1–5. 1 indexed citations
3.
Addeo, Pietro, Benoît Naegel, Chloé Paul, et al.. (2021). Predicting the available space for liver transplantation in cirrhotic patients: a computed tomography-based volumetric study. Hepatology International. 15(3). 780–790. 2 indexed citations
4.
Addeo, Pietro, et al.. (2021). Analysis of factors associated with discrepancies between predicted and observed liver weight in liver transplantation. Liver International. 41(6). 1379–1388. 4 indexed citations
5.
Addeo, Pietro, Vincent Noblet, Benoît Naegel, & Philippe Bachellier. (2020). Large-for-Size Orthotopic Liver Transplantation: a Systematic Review of Definitions, Outcomes, and Solutions. Journal of Gastrointestinal Surgery. 24(5). 1192–1200. 22 indexed citations
6.
Passat, Nicolas, Hugues Talbot, Benoît Naegel, et al.. (2020). Shaping for PET image analysis. Pattern Recognition Letters. 131. 307–313. 4 indexed citations
7.
Naegel, Benoît, et al.. (2020). Random walkers on morphological trees: A segmentation paradigm. Pattern Recognition Letters. 141. 16–22.
8.
Naegel, Benoît, et al.. (2019). Shape-Based Analysis on Component-Graphs for Multivalued Image Processing. SHILAP Revista de lepidopterología. 5 indexed citations
9.
Burgeth, Bernhard, et al.. (2019). Mathematical Morphology and Its Applications to Signal and Image Processing. Lecture notes in computer science. 22 indexed citations
10.
Valitutti, Salvatore, et al.. (2017). Optimal cut in minimum spanning trees for 3-D cell nuclei segmentation. SPIRE - Sciences Po Institutional REpository. 47. 195–199. 4 indexed citations
11.
Naegel, Benoît, Germain Forestier, Ralf Schönmeyer, et al.. (2016). Detection of lobular structures in normal breast tissue. Computers in Biology and Medicine. 74. 91–102. 16 indexed citations
12.
Naegel, Benoît, et al.. (2016). Joint 3D alignment-reconstruction multi-scale approach for cryo electron tomography. SPIRE - Sciences Po Institutional REpository. 1109–1113. 1 indexed citations
13.
Naegel, Benoît, et al.. (2014). Fast Segmentation for Texture-based Cartography of whole Slide Images. SPIRE - Sciences Po Institutional REpository. 309–319. 1 indexed citations
14.
Passat, Nicolas & Benoît Naegel. (2013). Component-Trees and Multivalued Images: Structural Properties. Journal of Mathematical Imaging and Vision. 49(1). 37–50. 20 indexed citations
15.
Tankyevych, Olena, Benoît Naegel, Hugues Talbot, et al.. (2012). Filtering and segmentation of 3D angiographic data: Advances based on mathematical morphology. Medical Image Analysis. 17(2). 147–164. 43 indexed citations
16.
Passat, Nicolas & Benoît Naegel. (2011). Component-trees and multivalued images-Part I: Structural Properties. 10. 1 indexed citations
17.
Naegel, Benoît, et al.. (2009). SNR enhancement of highly-accelerated real-time cardiac MRI acquisitions based on non-local means algorithm. Medical Image Analysis. 13(4). 598–608. 15 indexed citations
18.
Naegel, Benoît & Laurent Wendling. (2009). COMBINING SHAPE DESCRIPTORS AND COMPONENT-TREE FOR RECOGNITION OF ANCIENT GRAPHICAL DROP CAPS. SPIRE - Sciences Po Institutional REpository. 297–302. 4 indexed citations
19.
Naegel, Benoît, et al.. (2007). Segmentation using vector-attribute filters: methodology and application to dermatological imaging. ArODES (HES-SO (https://www.hes-so.ch/)). 239–250. 15 indexed citations
20.
Naegel, Benoît. (2007). Using mathematical morphology for the anatomical labeling of vertebrae from 3D CT-scan images. Computerized Medical Imaging and Graphics. 31(3). 141–156. 45 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Yung-Nien Sun Breakdown of academic impact, for papers by Xuehu Wang Breakdown of academic impact, for papers by Lars Aurdal Breakdown of academic impact, for papers by Bruno M. Carvalho Breakdown of academic impact, for papers by Shuqian Luo Breakdown of academic impact, for papers by Tianyu Shi Breakdown of academic impact, for papers by Changfa Shi Breakdown of academic impact, for papers by Heran Yang
Rankless by CCL
2026