Tackling Thousands of Cells: Annotating My Deep Learning Dataset
Tackling Thousands of Cells: Annotating My Deep Learning Dataset
Hey friend,
I’m building a custom deep learning model for analyzing coculture images – think thousands of cells per image! I’ve got about 1290 TIFF images to work with, and I need to create the ground truth data by meticulously annotating each cell. The problem is, there are thousands of cells per image, and manually doing this is, well, terrifying.
The reason I’m going through all this trouble is because I already tried a cell-counting pipeline, and it massively overestimated the number of leukemic cells due to undersegmentation. So, I need to create much more accurate annotations to train a better model.
My big question is: what’s the most efficient way to tackle this massive annotation task? What tools are best suited for handling this volume of data? Any suggestions would be incredibly helpful!
I’m thinking I need something powerful enough to handle the sheer number of cells, but also user-friendly enough to avoid driving myself crazy. Let me know what you think!
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