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Analise de imagens do exame Papanicolau para dar o diagnóstico precoce do câncer cervical. Aplicativo para ler imagens do exame para reconhecer automáticamente células cancerosas.

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brunofaria27/image-processing

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Documentation Acess

To access the documentation, simply click here. However, at the moment we only have the documentation in Portuguese in the form of an article. Nothing to add to the README.

CRIC Cervix Cell Classification - CSV Description

400 images from microscope slides of the uterine cervix using the conventional smear (Pap smear) and the epithelial cell abnormalities classified according to Bethesda system.

Data Fields

  • image_id This is the integer that identifies the image at http://database.cric.com.br/.
  • image_filename This is the name that identifies the image in the ZIP file that you have.
  • image_doi This is the DOI that identifies the image.
  • cell_id This is the integer that identifies the cell at http://database.cric.com.br/.
  • bethesda_system Classification of the cell using the Bethesda system. It is on of the following:
    • Negative for intraepithelial lesion
    • ASC-US Atypical squamous cells of undetermined significance
    • ASC-H Atypical squamous cells cannot exclude HSIL
    • LSIL Low grade squamous intraepithelial lesion
    • HSIL High grade squamous intraepithelial lesion
    • SCC Squamous cell carcinoma
  • nucleus_x Integer between 1 and 1384 equal to coordinate x of the pixel that represent the cell.
  • nucleus_y Integer between 1 and 1384 equal to coordinate y of the pixel that represent the cell.

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Analise de imagens do exame Papanicolau para dar o diagnóstico precoce do câncer cervical. Aplicativo para ler imagens do exame para reconhecer automáticamente células cancerosas.

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