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Sectra (Sweden)

Sweden

12 papers here629 citations across 12
fields
  • physics.med-ph7
  • cs.CV4
  • physics.ins-det1
ROR 025nk1308OpenAlex

affiliations via OpenAlex

output
20182026
most citedPredicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge

331 citations

researchers with a paper here
  • E. Fredenberg8 · h 15
  • M. Danielsson2 profiles8 · h 32
  • M. Aslund7 · h 11
  • M. Lundqvist4 · h 22
  • B. Cederström3 · h 13
  • B. Cederstrom2 · h 6
  • Björn Cederström2
  • C. Lundström2 · h 24
  • G. Eilertsen2 · h 17
  • M. Hemmendorff2 · h 7
  • Milda Pocevičiūtė2 · h 5
  • Andrew H. Beck1 · h 54
collaborating institutions
  • KTH Royal Institute of TechnologySE8 papers
  • AlbaNovaSE4 papers
  • Linköping UniversitySE3 papers
  • Beihang UniversityCN1 paper
  • Beth Israel Deaconess Medical CenterUS1 paper
  • Charité - Universitätsmedizin BerlinDE1 paper
  • Eindhoven University of TechnologyNL1 paper
  • German Cancer Research CenterDE1 paper
  • Harvard UniversityUS1 paper
  • Heidelberg UniversityDE1 paper
  • IBM (Brazil)BR1 paper
  • IBM Research - BrazilBR1 paper
Showing 2024Show all

1 paper · 1 filter

cs.CV2024★ 8 cited

Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance

Milda Pocevičiūtė, Gabriel Eilertsen, Stina Garvin +1

Multiple-instance learning (MIL) is an attractive approach for digital pathology applications as it reduces the costs related to data collection and labelling. However, it is not c…

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