Blood Cancer – Image 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).

Citations:

“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. https://doi.org/10.7937/tcia.2019.36f5o9ld

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). https://doi.org/10.1038/s42256-019-0101-9

Conclusion

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.