I’m using AI to Change the Game for 3D Microscopy Cell Segmentation

Can you guess how big a single microscopic 3D image of a mouse retina is? It’s about 10 Terabytes! That’s roughly equal to thousands of high-definition movies stored in just one image.

During my time at Siegert Lab, I was fascinated but also concerned when I realized scientists were manually segmenting microglial cells from these massive 3D confocal microscopy images. Imagine the effort, time, and potential for errors involved in manually processing data of this scale.

(Placeholder for photo: Scientists manually segmenting cells)

Introducing trAIce3D: A New AI model for cell segmentation

Motivated by this significant challenge, I developed trAIce3D, a cutting-edge deep-learning model designed specifically for the automatic and precise segmentation of microglial cells.

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