4D Minecraft cell models from label-free optical imaging (Conference Presentation)

There is a substantial opportunity to utilize the vast amount of data generated by modern biophotonics for education. We built an easy-to-use and general-purpose Python based framework for translating image data into the videogame Minecraft. Using data from label-free microscopy, we created Minecraft models comparing normal and cancerous breast cells, and timelapse models showing phorbol myristate acetate activation in neutrophils. We created a soundscape that changes based on the player’s interaction with the cells. These Minecraft models are easily accessible, providing engaging learning of biology and optical imaging.