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Pigeons 'as good as humans' at spotting cancer signs

Published 18/11/2015

Pigeons can be taught to recognise images showing evidence of benign or malignant tissue, scientists say
Pigeons can be taught to recognise images showing evidence of benign or malignant tissue, scientists say

One way to cut NHS spending might be to employ pigeons as cancer-screening pathologists, research suggests.

It may not be as bird-brained an idea as it sounds. A study has found that with the right training, pigeons are as good as humans at spotting signs of breast cancer in biopsy samples and mammogram scans.

Previous research had already shown that the common pigeon, Columba livia, has an extraordinary ability to categorise a wide range of objects and images.

They can distinguish between human faces and expressions, letters of the alphabet, and even paintings by different artists.

To test their abilities even further, scientists cast a group of pigeons in the role of pathologists and radiologists helping to diagnose breast cancer.

The birds were taught how to recognise microscope slides and mammogram scan images showing evidence of benign or malignant tissue.

They proved especially adept at sorting out the slide samples, the scientists found.

Lead researcher Professor Richard Levenson, from the University of California at Davis, US, said: "With some training and selective food reinforcement, pigeons do just as well as humans in categorising digitised slides and mammograms of benign and malignant human breast tissue.

"The birds were remarkably adept at discriminating between benign and malignant breast cancer slides at all magnifications, a task that can perplex inexperienced human observers, who typically require considerable training to attain mastery.

"Pigeons' accuracy from day one of training at low magnification increased from 50% correct to nearly 85% correct at days 13 to 15."

They were also as good as human radiologists at detecting microscopic calcification spots on mammograms that can be an early sign of cancer.

But the birds found it much more difficult to classify suspicious masses on the scans - a task described as "very challenging" even for expert humans.

After learning to distinguish between subtle differences in the scans during training, they failed to perform at a level better than chance when shown novel images they had not seen before.

As with humans, the accuracy of the pigeons was affected by the presence or absence of colour in the images, and degrees of image compression.

Co-author Professor Edward Wasserman, from the University of Iowa, US, said: "These results go a long way toward establishing a profound link between humans and our animal kin.

"Even distant relatives - like people and pigeons - are adept at perceiving and categorising the complex visual patterns that are presented in pathology and radiology images, surely a task for which nature has not specifically prepared us."

Pigeons have a brain no bigger than the tip of an index finger, but possess neural pathways strikingly similar to those at work in the human brain, said the scientists, whose findings appear in the online journal Public Library of Science ONE.

A total of eight pigeons took part in the experiment. Using food rewards, birds were trained to peck a blue or yellow "report button" depending on whether they were being shown a benign or malignant image.

Physicians sometimes struggle to interpret microscopic slides and mammograms even after years of education and training, Prof Levenson pointed out.

He seriously suggested giving pigeons a role in the development of new diagnostic procedures.

"While new technologies are constantly being designed to enhance image acquisition, processing, and display, these potential advances need to be validated using trained observers to monitor quality and reliability," said Prof Levenson. "This is a difficult, time-consuming, and expensive process that requires the recruitment of clinicians as subjects for these relatively mundane tasks.

"Pigeons' sensitivity to diagnostically salient features in medical images suggest that they can provide reliable feedback on many variables at play in the production, manipulation, and viewing of these diagnostically crucial tools, and can assist researchers and engineers as they continue to innovate."

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