Seventy five, 1000 × 1000 high quality regions were identified and extracted from the TMA images and saved as tiff images. Expert pathologists independently annotated these images. The annotations were done using Cellthon, a python based cell annotation graphical user interface (GUI) we created using Tkinter toolkit55 . Together these 75 images and their cell and nucleus annotations comprise the GIT dataset.
Cyclic Immunofluorescence Imaging of FFPE TMA
Seventy five, 1000 × 1000 high quality regions were identified and extracted from the TMA images and saved as tiff images. Expert pathologists independently annotated these images. The annotations were done using Cellthon, a python based cell annotation graphical user interface (GUI) we created using Tkinter toolkit55 . Together these 75 images and their cell and nucleus annotations comprise the GIT dataset.
Corresponding Organization : UPMC Hillman Cancer Center
Other organizations : Case Western Reserve University, University Hospitals of Cleveland, Magee-Womens Research Institute, University of Southern California
Variable analysis
- Antigen retrieval protocol
- Antibody dilutions (1:200 for Anti-Sodium Potassium ATPase, 1:100 for P53, 1:50 for EZH2, 1:100 for LAMIN A/C)
- Cell and nucleus annotations in the 75 TMA images
- Tissue TMA slides obtained from Pantomics and University of Pittsburgh Medical Center Presbyterian Hospital
- Overnight incubation of antibodies at 4°C in the dark
- Hoechst 33342 staining for 10 minutes at room temperature in the dark
- Imaging using a 0.95 NA and a 40X objective on a Nikon Ti2E microscope
- Not explicitly mentioned
- Not explicitly mentioned
Annotations
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