The continuous improvement of imaging technology holds great promise in areas where visual detection is necessary, such as with cancer screening. Three-dimensional imaging in particular has become popular because it provides a more complete picture of the target object and its context. However, with all this additional information provided, the rate of detection success does not always increase. In a paper recently published in the journal Current Biology, PBS professor Miguel Eckstein, lead author Miguel Lago and their collaborators point out an odd foible of human vision: We’re actually worse at finding small targets in 3D image stacks than if they were in a single 2D image.

“What happens is when doctors are looking through these 3D images, they basically underexplore the whole data set,” Prof. Eckstein explained. “They’re not looking at every single spot on every single image, because it takes a long time.”

For more about this story, please read this Current article by Sonia Fernandez.