Digital Imaging for Blood Diseases
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Scope of this subject
This cluster of papers focuses on the automated analysis of blood cell images, particularly in the context of detecting malaria parasites and classifying leukemia. The research utilizes techniques such as image processing, convolutional neural networks, and machine learning for tasks including white blood cell segmentation, feature extraction, and automated diagnosis from microscopic blood images.
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Research vocabulary
blood smear images; white blood cell classification; blood cell classification; leukemia detection; malaria parasite detection; leukocyte classification; automated microscopy; white blood cell segmentation; blood cell images; blood smear examination; blood cell detection; blood cell segmentation; blood cell image analysis; thin blood smear; white blood cell detection; automated blood cell counting; blood smear microscopy; leukocyte segmentation; anemia detection; automated blood smear analysis; automated blood cell classification; automated parasite detection; blood cell image classification; microscopic blood images; peripheral blood smear images
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Numeric address and provenance
Morton address: 38285820725215447 · morton4x16-v1
Coordinates: (3, 17, 1707, 12874). The address interleaves categorical identifier bits. Nearby addresses are not guaranteed to describe semantically similar subjects.
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