Public articles linked to the same research event.
Biology of reproduction The study developed a HALO AI-based placental tissue classifier that uses PLAP and DAPI staining to segment sections into villous core, villous trophoblast (VT), and intervillous space (IVS), validated area and intensity measurement in classified regions with SDC-1 and vimentin staining, and increased the area of staining analyzed to 245 times that of a single field of view on whole slide scanning images.
The study developed a HALO AI-based placental tissue classifier that uses PLAP and DAPI staining to segment sections into villous core, villous trophoblast (VT), and intervillous space (IVS), validated area and intensity measurement in classified regions with SDC-1 and vimentin staining, and increased the area of staining analyzed to 245 times that of a single field of view on whole slide scanning images.
The study developed a HALO AI-based placental tissue classifier that uses PLAP and DAPI staining to segment sections into villous core, villous trophoblast (VT), and intervillous space (IVS), validated area and intensity measurement in classified regions with SDC-1 and vimentin staining, and increased the area of staining analyzed to 245 times that of a single field of view on whole slide scanning images.
The study developed a HALO AI-based placental tissue classifier that uses PLAP and DAPI staining to segment sections into villous core, villous trophoblast (VT), and intervillous space (IVS), validated area and intensity measurement in classified regions with SDC-1 and vimentin staining, and increased the area of staining analyzed to 245 times that of a single field of view on whole slide scanning images.