Machine Learning-based Segmentation
Machine Learning-Based Segmentation is a computational method that uses machine learning algorithms to automatically partition patient or volume data into distinct, meaningful subgroups or regions based on learned patterns from training data, distinguishing it from traditional rule-based or manual segmentation techniques.
320
Publications
18.7K
Citations
1.5K
Authors
668
Institutions
Publications per year
2017–2026
227
320
Ilastik: Interactive learning and segmentation toolkit
Christoph Sommer, Christoph Straehle, Ullrich Köthe et al. · 2011 · 1.2K citations
José Ignacio Orlando, Elena Prokofyeva, Matthew B. Blaschko · IEEE Transactions on Biomedical Engineering · 2016 · 514 citations · Full text
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668
Heidelberg University
Heidelberg, Germany
8 h-index
32 publications
6.4K citations
Harvard University
Cambridge, United States
7 h-index
14 publications
4K citations

University Hospital Heidelberg
Heidelberg, Germany
6 h-index
19 publications
684 citations
University College London
London, United Kingdom
6 h-index
27 publications
2K citations

Chinese Academy of Sciences
Beijing, China
6 h-index
9 publications
1.3K citations
German Cancer Research Center
Heidelberg, Germany
5 h-index
22 publications
1.4K citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
11 publications
624 citations
Vellore Institute of Technology University
Vellore, India
5 h-index
8 publications
366 citations
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8 publications · 1.9K citations
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6 publications · 508 citations
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6 publications · 314 citations
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5 publications · 165 citations
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Repository · 5 publications · 265 citations
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