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institution

Swedish Medical Center

United States

3 papers here128 citations across 3
fields
  • cs.IR1
  • cs.NI1
  • eess.IV1
ROR 004jktf35OpenAlex

affiliations via OpenAlex

output
20092021
most citedSinGAN-Seg: Synthetic training data generation for medical image segmentation

126 citations

researchers with a paper here
  • C. Boano1 · h 29
  • H. Hammer1 · h 15
  • K. Römer1 · h 34
  • Marco Zúñiga1 · h 29
  • M. Boman1 · h 21
  • M. Riegler1 · h 50
  • Olof Görnerup1 · h 9
  • Pål Halvorsen1
  • Pegah Salehi1 · h 10
  • Sajad Amouei Sheshkal1 · h 3
  • S. Parasa1 · h 28
  • Steven Hicks1 · h 25
collaborating institutions
  • Swedish InstituteSE2 papers
  • Delft University of TechnologyNL1 paper
  • Institut für Technische und Angewandte Physik (Germany)DE1 paper
  • OsloMet – Oslo Metropolitan UniversityNO1 paper
  • Sahlgrenska University HospitalSE1 paper
  • Simula Metropolitan Center for Digital EngineeringNO1 paper
  • University of GothenburgSE1 paper
Showing eess.IVShow all

1 paper · 1 filter

eess.IV2021★ 126 cited

SinGAN-Seg: Synthetic training data generation for medical image segmentation

Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal +6

Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Artificial…

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