Remco Duits

2.8k total citations · 1 hit paper
72 papers, 1.1k citations indexed

About

Remco Duits is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Applied Mathematics. According to data from OpenAlex, Remco Duits has authored 72 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Radiology, Nuclear Medicine and Imaging, 32 papers in Computer Vision and Pattern Recognition and 12 papers in Applied Mathematics. Recurrent topics in Remco Duits's work include Advanced Neuroimaging Techniques and Applications (21 papers), Medical Image Segmentation Techniques (20 papers) and Image and Signal Denoising Methods (13 papers). Remco Duits is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (21 papers), Medical Image Segmentation Techniques (20 papers) and Image and Signal Denoising Methods (13 papers). Remco Duits collaborates with scholars based in Netherlands, France and Russia. Remco Duits's co-authors include Bart M. ter Haar Romeny, Erik Franken, Erik J. Bekkers, Jiong Zhang, Behdad Dashtbozorg, Josien P. W. Pluim, Luc Florack, Michael Felsberg, Gösta H. Granlund and Francesco Rossi and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Medical Imaging.

In The Last Decade

Remco Duits

69 papers receiving 1.1k citations

Hit Papers

Robust Retinal Vessel Segmentation via Locally Adaptive D... 2016 2026 2019 2022 2016 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Remco Duits Netherlands 18 572 557 280 120 106 72 1.1k
Luc Florack Netherlands 19 379 0.7× 1.1k 2.1× 14 0.1× 80 0.7× 121 1.1× 101 1.8k
Mikaël Rousson United States 16 424 0.7× 1.4k 2.5× 10 0.0× 15 0.1× 39 0.4× 23 1.8k
V. Caselles Spain 9 99 0.2× 2.3k 4.2× 18 0.1× 74 0.6× 30 0.3× 13 2.8k
Attila Kuba Hungary 16 549 1.0× 880 1.6× 12 0.0× 19 0.2× 11 0.1× 69 1.2k
Tomeu Coll Spain 3 260 0.5× 1.8k 3.3× 17 0.1× 51 0.4× 11 0.1× 3 2.3k
Rongjie Lai United States 18 130 0.2× 399 0.7× 6 0.0× 18 0.1× 51 0.5× 60 1.0k
J.F. Boyce United Kingdom 23 2.2k 3.8× 942 1.7× 2.4k 8.6× 13 0.1× 14 0.1× 97 3.1k
Hongqing Zhu China 18 132 0.2× 1.1k 1.9× 17 0.1× 22 0.2× 32 0.3× 104 1.5k
Oleg Michailovich Canada 22 911 1.6× 715 1.3× 4 0.0× 25 0.2× 132 1.2× 65 1.7k
Chunhong Cao China 13 267 0.5× 440 0.8× 148 0.5× 6 0.1× 20 0.2× 54 893

Countries citing papers authored by Remco Duits

Since Specialization
Citations

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

Fields of papers citing papers by Remco Duits

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Remco Duits

This figure shows the co-authorship network connecting the top 25 collaborators of Remco Duits. A scholar is included among the top collaborators of Remco Duits 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 Remco Duits. Remco Duits 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.
Smets, Bart, et al.. (2025). PDE-CNNs: Axiomatic Derivations and Applications. Journal of Mathematical Imaging and Vision. 67(2). 1 indexed citations
2.
Duits, Remco, et al.. (2024). Loss function inversion for improved crack segmentation in steel bridges using a CNN framework. Automation in Construction. 170. 105896–105896. 5 indexed citations
3.
Smets, Bart, et al.. (2023). Analysis of (sub-)Riemannian PDE-G-CNNs. Journal of Mathematical Imaging and Vision. 65(6). 819–843. 3 indexed citations
4.
Leonetti, Davide, et al.. (2023). Probability of detection curve for the automatic visual inspection of steel bridges. ce/papers. 6(3-4). 814–824. 1 indexed citations
5.
Xing, Jie, et al.. (2019). Automated Segmentation of Lesions in Ultrasound Using Semi-pixel-wise Cycle Generative Adversarial Nets.. arXiv (Cornell University). 7 indexed citations
6.
Duits, Remco, et al.. (2018). Optimal Paths for Variants of the 2D and 3D Reeds–Shepp Car with Applications in Image Analysis. Journal of Mathematical Imaging and Vision. 60(6). 816–848. 34 indexed citations
7.
Janssen, A. J. E. M., et al.. (2018). Design and Processing of Invertible Orientation Scores of 3D Images. Journal of Mathematical Imaging and Vision. 60(9). 1427–1458. 9 indexed citations
8.
Ossenblok, Pauly, Louis Wagner, Olaf Schijns, et al.. (2017). Stability metrics for optic radiation tractography: Towards damage prediction after resective surgery. Journal of Neuroscience Methods. 288. 34–44. 6 indexed citations
9.
Duits, Remco, et al.. (2016). A Cortical Based Model for Contour Completion on the Retinal Sphere. Program systems theory and applications. 7(4). 231–247. 1 indexed citations
10.
Garyfallidis, Eleftherios, et al.. (2016). Fast implementations of contextual PDE's for HARDI data processing in DIPY. TU/e Research Portal. 1 indexed citations
11.
Fick, Rutger, et al.. (2015). Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution. PLoS ONE. 10(10). e0138122–e0138122. 17 indexed citations
12.
Duits, Remco, et al.. (2014). Left-invariant evolutions of wavelet transforms on the similitude group. Applied and Computational Harmonic Analysis. 39(1). 110–137. 2 indexed citations
13.
Duits, Remco, Ugo Boscain, Francesco Rossi, & Yu. L. Sachkov. (2013). Association Fields via Cuspless Sub-Riemannian Geodesics in SE(2). Journal of Mathematical Imaging and Vision. 49(2). 384–417. 28 indexed citations
14.
Bekkers, Erik J., et al.. (2012). A new retinal vessel tracking method based on orientation scores. arXiv (Cornell University). 33(9). 1200–1. 3 indexed citations
15.
Duits, Remco, et al.. (2010). Cardiac motion estimation using covariant derivatives and Helmholtz decomposition. TU/e Research Portal (Eindhoven University of Technology). 1031. 1 indexed citations
16.
Duits, Remco, et al.. (2009). Diffusion on the 3D Euclidean motion group for enhancement of HARDI data. TU/e Research Portal (Eindhoven University of Technology). 902. 1 indexed citations
17.
Franken, Erik & Remco Duits. (2008). Crossing-preserving coherence-enhancing diffusion on invertible orientation scores. TU/e Research Portal (Eindhoven University of Technology). 803. 1 indexed citations
18.
Duits, Remco. (2005). Perceptual organization in image analysis:a mathematical approach based on scale, orientation and curvature. Data Archiving and Networked Services (DANS). 4 indexed citations
19.
Duits, Remco, et al.. (2004). Image processing via shift-twist invariant operations on orientation bundle functions. Pattern Recognition and Image Analysis. 15(1). 151–156. 6 indexed citations
20.
Duits, Remco, et al.. (2003). Alpha scale spaces on a bounded domain. TU/e Research Portal. 8 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.

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