Peeling back the layers
18 Oct 2010 by Evoluted New Media
Historical works of art are prone to damage and deterioration, and scientists using Optical Coherence Tomography (OCT) have just received a £600,000 grant to improve the technique to help restore masterpieces.
Historical works of art are prone to damage and deterioration, and scientists using Optical Coherence Tomography (OCT) have just received a £600,000 grant to improve the technique to help restore masterpieces.
One of da Vinci’s most famous paintings can now be visualised using OCT |
Dr Haida Liang first realised in 2004 that OCT – normally a medical imaging tool – could be used to reveal the distribution of paint and varnish and even the artist’s preparatory drawings which can be used by art conservators to preserve the paintings.
Liang and her colleagues at Nottingham Trent University’s School of Science and Technology have just been awarded £600,000 by the Arts and Humanities Research Council (AHRC) and the Engineering and Physical Sciences Research Council (EPSRC) to improve the level of information that can be gained through OCT.
“I am very excited about where we can take our research with this funding,” she said, “I’m confident that we’ll continue to develop and refine the technology in a way that will see it making an even greater contribution to the world of art conservation and archaeology.”
The researchers hope to make a variety of improvements – including developing a system which uses broader band and longer wavelength of light – to improve the resolution and depth of penetration that can be achieved through this non-invasive technique. It is hoped the improvements will allow conservators to collect a level of detail currently only possible by removing samples and examining under a microscope.
OCT involves using infrared light to penetrate a material – in this case painting but usually biological tissues – which scatters the light back. This scattered light is detected by the machine, which measures the distance it has travelled and results in a three-dimensional image of the inner structure.