Blood Cancer – Image Dataset

Blood Cancer – Image Dataset


Blood Cancer – Image Dataset


Cancer – Image Dataset

Use Case

Diagnosis Aid


A "Cancer - Image Dataset" typically refers to a collection of medical images, such as blood smears or bone marrow samples, that have been used for research and analysis in the field of hematology, particularly for the detection and classification of blood-related cancers, such as leukemia and lymphoma.

About Dataset

This dataset has 10,000 images of single cells, each measuring 64×64 pixels. These images were taken from blood smears of patients diagnosed with Acute Myeloid Leukemia, which is a type of blood cancer.

The images were obtained from The Cancer Imaging Archive (TCIA).


“Matek, C., Schwarz, S., Marr, C., & Spiekermann, K. (2019). A Single-cell Morphological Dataset of Leukocytes from AML Patients and Non-malignant Controls [Data set]. The Cancer Imaging Archive.

Matek, C., Schwarz, S., Spiekermann, K. et al. Human-level recognition of blast cells in acute myeloid leukaemia with convolutional neural networks. Nat Mach Intell 1, 538–544 (2019).


In the end, just like a movie based on a book, the worth of blood cancer image datasets depends on their quality and ethical handling.

A collection of images of blood cancer can be incredibly helpful for doctors and researchers. It can greatly improve our ability to diagnose and study this disease. Such a dataset can help us identify the exact type of blood cancer, choose the best treatment options, advance research efforts, and serve as a valuable learning tool. However, the real measure of these datasets is their quality and whether they adhere to ethical standards.

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