Seeded Segmentation
Seeded Segmentation is a volume segmentation method that incorporates user-defined or algorithmically generated initial markers, or "seeds," to guide the delineation of regions through region-growing, graph-based, or probabilistic inference techniques, thereby distinguishing it from unseeded or fully automated segmentation approaches.
95
Publications
9.7K
Citations
316
Authors
146
Institutions
Publications per year
2017–2026
14
Variants
Seed-based Segmentation
Parents
95
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing
Zilong Huang, Xinggang Wang, Jiasi Wang et al. · 2018 · 635 citations
1–5 of 95
316
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 316
146
Universidade de São Paulo
São Paulo, Brazil
5 h-index
9 publications
251 citations

Universiti Teknologi MARA
Shah Alam, Malaysia
3 h-index
13 publications
385 citations
National Central University
Taoyuan City, Taiwan
3 h-index
5 publications
220 citations
University of California, Davis
Davis, United States
3 h-index
6 publications
139 citations

Northwestern Polytechnical University
Xi'an, China
2 h-index
2 publications
167 citations
Brown University
Providence, United States
2 h-index
2 publications
76 citations
Shaanxi University of Science and Technology
Xi'an, China
2 h-index
2 publications
167 citations

Uppsala University
Uppsala, Sweden
2 h-index
8 publications
1.5K citations
1–8 of 146
5 publications · 125 citations
5
h-index
3 publications · 868 citations
3
h-index
TPAMI · 3 publications · 3.2K citations
3
h-index
2 publications · 592 citations
2
h-index
2 publications · 184 citations
2
h-index
1–5