A new x-ray technique that works alongside a deep-learning algorithm to detect explosives in luggage could eventually catch potentially deadly tumors in humans.
[...] While standard x-ray machines hit objects with a uniform field of x-rays, the team scanned the bags using a custom-built machine containing masks—sheets of metal with holes punched into them, which separate the beams into an array of smaller beamlets.
As the beamlets passed through the bag and its contents, they were scattered at angles as small as a microradian (around one 20,000th as big as a degree).The scattering was analyzed by AI trained to recognize the texture of specific materials from a particular pattern of angle changes.
The AI is exceptionally good at picking up these materials even when they're hidden inside other objects, says lead author Sandro Olivo, from the UCL Department of Medical Physics and Biomedical Engineering. "Even if we hide a small quantity of explosive somewhere, because there will be a little bit of texture in the middle of many other things, the algorithm will find it."
[...] The technique could also be used in medical applications, particularly cancer screening, the team believes. Although the researchers are yet to test whether the technique could successfully differentiate the texture of a tumor from surrounding healthy breast tissue, for example, he's excited by the possibility of detecting very small tumors that could previously have gone undetected behind a patient's rib cage.
[...] But the human body is a significantly more challenging environment to scan than static, air-filled objects like bags, points out Kevin Wells, associate professor at the University of Surrey, who was not involved in the study. Additionally, the researchers would need to downsize the bulky equipment and ensure that the cost was equivalent to that of existing techniques before it could be considered as a potential screening method for humans.
Journal Reference:
Partridge, T., Astolfo, A., Shankar, S. S., et al. Enhanced detection of threat materials by dark-field x-ray imaging combined with deep neural networks [open], Nature Communications (DOI: 10.1038/s41467-022-32402-0)
(Score: 4, Insightful) by janrinok on Saturday September 17 2022, @06:21PM
This is why I like science - it is the things that we discover which were not the prime reason for the experiment and development in the first instance.
Developing equipment to identify explosives is a worthwhile goal, but if it does prove to be useful for detecting tumours then it might be for this purpose that it becomes a much bigger contribution to saving even more lives than it was originally planned to do.