Commercial

Mammography Segmentation Dataset

Dataset of x-ray of the mammary includes over 3,000 studies that highlight various pathologies such as skin thickening, papilloma, lymph node and etc.

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  • Medicine The use of machine learning in the medicine
  • Segmentation Dividing an image into semantically independent segments to determine object boundaries
  • Computer Vision The ability to recognize and analyze images and videos
  • Classification Process of recognition and grouping of objects into preset categories
    3,000+
    studies
    14+
    pathologies
Example of a study

CASE DESCRIPTION

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The dataset contains 3000 studies. The data format is dicom.

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It includes detailed segmentation masks for 14 pathologies

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The dataset is annotated by the professional medics for segmentation tasks. The annotation is stored in json format

Example of a study
Example of a study
Example of a study
Example of a study
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Application areas of the dataset

  • 01.

    Medical diagnostics:

    Computer vision and classification for automatic detection and classification of various mammary glands pathologies
  • 02.

    Clinical Decision Support Systems:

    The dataset can enhance decision-making tools by providing accurate segmentation data that assist healthcare professionals in interpreting X-ray
  • 03.

    Training Medical Personnel:

    Segmentation for the education and training of medical university students, interns, and residents

Pathologies

  • Skin thickening
  • papilloma
  • malignant lesion
  • benign lesion
  • malignant calcification cluste
  • calcified vessel
  • artifact
  • calcified cyst
  • lymph node
  • fibrocystic changes
  • single calcification
  • nipple
  • retracted nipple
  • others

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