Pioneering Technical Developments in Imagery: Month-long focus on research that is exploring far beyond what the human eye can see

""We humans are visual creatures. An image aims to depict reality to us, but also invokes our imagination. It speaks more than a thousand words. We live in a world saturated with images and images allow us to see this world – from brain cells to distant galaxies – as never before. Advanced imaging techniques enable us to ask new research questions, break down disciplinary boundaries and extend our knowledge across an immense variety of fields. 

Scientists have always used images of various kinds – drawings, pictures, photographs and videos, to name a few – to make discoveries, describe processes in nature, catalogue and achieve specimens, and illustrate observations and ideas. In scientific discoveries, images are often the scientific finding itself.

A work of art, an image in itself, can be analysed and its making can be understood with the help of advanced scientific imaging techniques. New images are created by this analysis, and the worlds of arts and science are becoming increasingly overlapping. 

Scientific imaging has never been as exciting as it is now, with new technologies emerging all the time. The resolution limit in light microscopy, which had seemed unbreakable, is now less than 100 nanometres. These advances in super-resolved fluorescence microscopy were recognised in  2014 by the awarding of the Nobel Prize in Chemistry to Eric Betzig and W. E. Moerner in the USA and Stefan Hell in Germany.

Cambridge is home to a wealth of research which includes developing tools for acquisition, visualisation, automated processing and analysis of images. In January 2014, a group was formed to connect, present, discuss and advance research on or with images. IMAGES brings together leading academics from across the disciplines, as well as international experts and research-led industries that work on pioneering imaging technologies and analytical algorithms.

The complex process, from acquiring images, to their interpretation and problem-solving applications, requires multi-expertise partnerships. Different problems and image applications inform similar methodologies and interpretative strategies. Cross-disciplinary collaboration is needed to analyse the image information not explicit in machine-generated data.

Mathematicians, physicists, chemists and biologists work together to develop new instruments, chemical dyes and model systems to interrogate biological questions with more precision and at greater resolution.""

Source Article: 

http://www.cam.ac.uk/research/discussion/imaging-interpreting-the-seen-and-discovering-the-unseen