Michaël Aertsen

55 papers receiving 2.0k citations

Michaël Aertsen's Hit Papers

Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks 2019 · 375 citations
3750+2+5Years since publication100200300400500

Peers

Michaël Aertsen
Comparison fields: 5 of 135
  • Health Informatics 47
  • Computer Vision and Pattern Recognition 687
  • Radiology, Nuclear Medicine and Imaging 542
  • Neurology 201
  • Pediatrics, Perinatology and Child Health 334
Replace Tom Doel with:
Tom Doel United Kingdom
María A. Zuluaga France
Premal A. Patel United Kingdom
Óscar Cámara Spain
Miguel Á. González Ballester Spain
Marius George Linguraru United States
Jie‐Zhi Cheng China
Xin Yang China
Fahmi Khalifa United States
Rosalind Pratt United Kingdom
Michaël Aertsen relative to Tom Doel United Kingdom Tom Doel's profile →
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Citations per year

Countries citing papers authored by Michaël Aertsen

Since Specialization
Citations

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

Fields of papers citing papers by Michaël Aertsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michaël Aertsen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michaël Aertsen Line = papers co-authored together Michaël Aertsen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning
Hit paper breakdown →
2018576
2
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
Hit paper breakdown →
2019375
3
DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation
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2018302
4 2019154
5 202177
6 201653
7 201646
8 202033
9 201531
10 201820
11 201919
12 201918
13 201518
14 202017
15 201915
16 202115
17 202115
18 202015
19
Test-time augmentation with uncertainty estimation for deep learning-based medical image segmentation
201815
20 202213

About Michaël Aertsen

Michaël Aertsen is a scholar working on Pediatrics, Perinatology and Child Health, Surgery, Public Health, Environmental and Occupational Health, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 62 papers that have together received 2.0k indexed citations. Recurring topics across this work include Fetal and Pediatric Neurological Disorders (18 papers), Spinal Dysraphism and Malformations (10 papers), Congenital Diaphragmatic Hernia Studies (9 papers), Prenatal Screening and Diagnostics (6 papers), Advanced Neural Network Applications (5 papers), Autopsy Techniques and Outcomes (4 papers), Medical Image Segmentation Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Health Informatics (47 citations), Computer Vision and Pattern Recognition (687 citations), Radiology, Nuclear Medicine and Imaging (542 citations), Neurology (201 citations) and Pediatrics, Perinatology and Child Health (334 citations). Michaël Aertsen has collaborated with scholars based in Belgium, United Kingdom and United States. Frequent co-authors include Jan Deprest, Tom Vercauteren, Sébastien Ourselin, Guotai Wang, Wenqi Li, Anna L. David, Tom Doel, Premal A. Patel, Rosalind Pratt and María A. Zuluaga. Their work appears in journals such as Ultrasound in Obstetrics and Gynecology, Prenatal Diagnosis, American Journal of Neuroradiology, American Journal of Obstetrics and Gynecology and European Journal of Medical Genetics.

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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