Mathieu De Craene

3.0k total citations · 1 hit paper
82 papers, 1.6k citations indexed

About

Mathieu De Craene is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mathieu De Craene has authored 82 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Radiology, Nuclear Medicine and Imaging, 40 papers in Cardiology and Cardiovascular Medicine and 27 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mathieu De Craene's work include Cardiovascular Function and Risk Factors (31 papers), Medical Image Segmentation Techniques (26 papers) and Advanced MRI Techniques and Applications (23 papers). Mathieu De Craene is often cited by papers focused on Cardiovascular Function and Risk Factors (31 papers), Medical Image Segmentation Techniques (26 papers) and Advanced MRI Techniques and Applications (23 papers). Mathieu De Craene collaborates with scholars based in Spain, France and Belgium. Mathieu De Craene's co-authors include Alejandro F. Frangi, Hélène Langet, Bernhard Gerber, Mihaela Amzulescu, Nicolás Duchateau, Jean‐Louis Vanoverschelde, David Vancraeynest, Anne–Catherine Pouleur, Agnès Pasquet and Gemma Piella and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Mathieu De Craene

80 papers receiving 1.5k citations

Hit Papers

Myocardial strain imaging: review of general principles, ... 2019 2026 2021 2023 2019 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Myocardial strain imaging: review of general principles, validation, and sources of discrepancies
    2019 298 citations Mathieu De Craene, Hélène Langet et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mathieu De Craene Spain 21 852 786 361 351 175 82 1.6k
Tommaso Mansi United States 24 646 0.8× 649 0.8× 481 1.3× 442 1.3× 135 0.8× 80 1.8k
Eigil Samset Norway 25 628 0.7× 605 0.8× 314 0.9× 444 1.3× 168 1.0× 103 1.7k
Patrick Clarysse France 22 1.1k 1.3× 687 0.9× 534 1.5× 388 1.1× 126 0.7× 95 1.8k
Constantine Butakoff Spain 21 311 0.4× 641 0.8× 364 1.0× 163 0.5× 112 0.6× 65 1.5k
Dirk Loeckx Belgium 21 580 0.7× 236 0.3× 490 1.4× 288 0.8× 220 1.3× 67 1.4k
Matthew McCormick United States 17 422 0.5× 296 0.4× 147 0.4× 332 0.9× 244 1.4× 54 1.0k
Anja Hennemuth Germany 25 769 0.9× 859 1.1× 193 0.5× 284 0.8× 523 3.0× 131 1.7k
A. Herment France 22 981 1.2× 617 0.8× 219 0.6× 459 1.3× 424 2.4× 96 1.7k
Joseph Y. Cheng United States 22 1.3k 1.5× 248 0.3× 302 0.8× 229 0.7× 123 0.7× 55 1.9k
Bernard Chiu Hong Kong 18 362 0.4× 420 0.5× 374 1.0× 179 0.5× 533 3.0× 88 1.1k

Countries citing papers authored by Mathieu De Craene

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu De Craene

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mathieu De Craene. 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 Mathieu De Craene. The network helps show where Mathieu De Craene may publish in the future.

Co-authorship network of co-authors of Mathieu De Craene

This figure shows the co-authorship network connecting the top 25 collaborators of Mathieu De Craene. A scholar is included among the top collaborators of Mathieu De Craene 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 Mathieu De Craene. Mathieu De Craene 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.
Langet, Hélène, et al.. (2021). Decision Tree Learning for Uncertain Clinical Measurements. Lirias (KU Leuven). 4 indexed citations
2.
Garza, María Sanz‐de la, Rosario J. Perea, Isabel Blanco, et al.. (2020). Three-dimensional regional bi-ventricular shape remodeling is associated with exercise capacity in endurance athletes. European Journal of Applied Physiology. 120(6). 1227–1235. 10 indexed citations
3.
Duchateau, Nicolás, Andrew P. King, & Mathieu De Craene. (2020). Machine Learning Approaches for Myocardial Motion and Deformation Analysis. Frontiers in Cardiovascular Medicine. 6. 190–190. 18 indexed citations
4.
Craene, Mathieu De, et al.. (2019). Analysis of nonstandardized stress echocardiography sequences using multiview dimensionality reduction. Medical Image Analysis. 60. 101594–101594. 5 indexed citations
5.
Alessandrini, Martino, Brecht Heyde, Olivier Bernard, et al.. (2017). Realistic Vendor-Specific Synthetic Ultrasound Data for Quality Assurance of 2-D Speckle Tracking Echocardiography: Simulation Pipeline and Open Access Database. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 65(3). 411–422. 32 indexed citations
6.
Piella, Gemma, Mathieu De Craene, Constantine Butakoff, et al.. (2013). Multiview diffeomorphic registration: Application to motion and strain estimation from 3D echocardiography. Medical Image Analysis. 17(3). 348–364. 16 indexed citations
7.
Hoogendoorn, Corné, Nicolás Duchateau, Damián Sánchez‐Quintana, et al.. (2012). A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT. IEEE Transactions on Medical Imaging. 32(1). 28–44. 66 indexed citations
8.
Duchateau, Nicolás, Mathieu De Craene, Gemma Piella, & Alejandro F. Frangi. (2012). Constrained manifold learning for the characterization of pathological deviations from normality. Medical Image Analysis. 16(8). 1532–1549. 18 indexed citations
9.
Craene, Mathieu De, Gemma Piella, Óscar Cámara, et al.. (2011). Temporal diffeomorphic free-form deformation: Application to motion and strain estimation from 3D echocardiography. Medical Image Analysis. 16(2). 427–450. 90 indexed citations
10.
Oubel, Estanislao, Mathieu De Craene, Alfred O. Hero, et al.. (2011). Cardiac motion estimation by joint alignment of tagged MRI sequences. Medical Image Analysis. 16(1). 339–350. 19 indexed citations
11.
Duchateau, Nicolás, Mathieu De Craene, Gemma Piella, et al.. (2011). A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities. Medical Image Analysis. 15(3). 316–328. 41 indexed citations
12.
Zhang, Chong, María-Cruz Villa-Uriol, Mathieu De Craene, et al.. (2011). Dynamic estimation of three‐dimensional cerebrovascular deformation from rotational angiography. Medical Physics. 38(3). 1294–1306. 7 indexed citations
13.
Piella, Gemma, Mathieu De Craene, Bart Bijnens, et al.. (2010). Characterizing Myocardial Deformation in Patients With Left Ventricular Hypertrophy of Different Etiologies Using the Strain Distribution Obtained by Magnetic Resonance Imaging. Revista Española de Cardiología (English Edition). 63(11). 1281–1291. 15 indexed citations
14.
Craene, Mathieu De, Gemma Piella, Nicolás Duchateau, et al.. (2010). Temporal Diffeomorphic Free-Form Deformation for Strain Quantification in 3D-US Images. Lecture notes in computer science. 13(Pt 2). 1–8. 12 indexed citations
15.
Cámara, Óscar, Steffen Oeltze, Mathieu De Craene, et al.. (2009). Cardiac Motion Estimation from Intracardiac Electrical Mapping Data: Identifying a Septal Flash in Heart Failure. Lecture notes in computer science. 5528. 21–29. 1 indexed citations
16.
Craene, Mathieu De, Óscar Cámara, Bart Bijnens, & Alejandro F. Frangi. (2009). Large Diffeomorphic FFD Registration for Motion and Strain Quantification from 3D-US Sequences. Lecture notes in computer science. 5528. 437–446.
17.
Larrabide, Ignacio, Pedro Omedas, Constantine Butakoff, et al.. (2009). GIMIAS: An Open Source Framework for Efficient Development of Research Tools and Clinical Prototypes. Lecture notes in computer science. 5528. 417–426. 1 indexed citations
18.
Duchateau, Nicolás, Mathieu De Craene, Etelvino Silva, et al.. (2009). Septal Flash Assessment on CRT Candidates Based on Statistical Atlases of Motion. Lecture notes in computer science. 12(Pt 2). 759–766. 6 indexed citations
19.
Zhang, Chong, María-Cruz Villa-Uriol, Mathieu De Craene, José M. Pozo, & Alejandro F. Frangi. (2009). Morphodynamic Analysis of Cerebral Aneurysm Pulsation From Time-Resolved Rotational Angiography. IEEE Transactions on Medical Imaging. 28(7). 1105–1116. 20 indexed citations
20.
Xivry, Jonathan Orban de, Guillaume Janssens, Geert Bosmans, et al.. (2007). Tumour delineation and cumulative dose computation in radiotherapy based on deformable registration of respiratory correlated CT images of lung cancer patients. Radiotherapy and Oncology. 85(2). 232–238. 59 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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