Improving unsupervised stain-to-stain translation using self-supervision and meta-learning

• Egile Nagusiak: Nassim Bouteldja (Egilea), Barbara M. Klinkhammer (Egilea), Tarek Schlaich (Egilea), Peter Boor (Egilea), Dorit Merhof (Egilea)
• Formatua: Liburua
• Argitaratua: Elsevier, 2022-01-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.

Background: In digital pathology, many image analysis tasks are challenged by the need for large and time-consuming manual data annotations to cope with various sources of variability in the image domain. Unsupervised domain adaptation based on image-to-image translation is gaining importance in thi...