MyData: A Comprehensive Database of Mycetoma Tissue Microscopic Images

This dataset provides the first comprehensive collection of histopathological images for the study and automated diagnosis of mycetoma, a neglected tropical disease. The dataset includes 864 microscopic images from 142 patients, annotated with binary masks for grain detection and segmentation. The images represent both eumycetoma (fungal, FM) and actinomycetoma (bacterial, BM) cases, offering a valuable resource for developing and evaluating AI models for disease classification and segmentation tasks. This dataset supports the advancement of digital pathology solutions.

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Title MyData: A Comprehensive Database of Mycetoma Tissue Microscopic Images
Description

This dataset provides the first comprehensive collection of histopathological images for the study and automated diagnosis of mycetoma, a neglected tropical disease. The dataset includes 864 microscopic images from 142 patients, annotated with binary masks for grain detection and segmentation. The images represent both eumycetoma (fungal, FM) and actinomycetoma (bacterial, BM) cases, offering a valuable resource for developing and evaluating AI models for disease classification and segmentation tasks. This dataset supports the advancement of digital pathology solutions.
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Contact points
Contact point 1
URI
Name
Health-RI servicedesk
Name (translations)
Email
servicedesk@health-ri.nl
Identifier
http://example.com/
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Publisher
Publisher 1
URI
Name
Health-RI
Name (translations)
Email
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http://health-ri.nl
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Creator 1
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Lamis Elkeir
Name (translations)
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Type
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http://example.com
Creator 2
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Hyam Ali
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http://example.com
Landing page
Release date 2024-12-09T10:47:27+00:00
Modification date 2024-12-09T10:47:27+00:00
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    Version
    Version notes
    Identifier https://xnat-acc.health-ri.nl/data/archive/projects/africai_miccai2024_maIcetoma
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    Spatial resolution in meters
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    Theme
    1. http://publications.europa.eu/resource/authority/data-theme/HEAL
    Language
    1. http://id.loc.gov/vocabulary/iso639-1/en
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    Health category
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    Number of records for unique individuals.
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    URI https://fdp-acc.healthdata.nl/dataset/e2dfd78b-a8c1-4e24-9458-ad215cd3fe69