Focussing effort where it is needed

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Until now we have simply sent all the images of each¬†M. tuberculosis sample growing on each and every of the 14 antibiotics out to be classified by the citizen scientists. A while ago we realised that some images are “easy” in the sense that all the volunteers we show it to all give exactly the same answer. So, with a bit of work behind the scenes, we’ve written some computer code that can detect where the wells are in each image and then measure the amount of growth in each well. Now, it is isn’t perfect; it can be confused by small amounts of growth and artefacts like air bubbles and shadows, but it does mean we can confidently filter out the relatively easy images, thereby allowing us to only send the more challenging cases to you, our volunteers.

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