Sound could deliver real-time cancer results

New research shows that converting medical data into sound could enable doctors to make instant cancer diagnoses during routine check-ups.

 

Dr Domenico Vicinanza, of Anglia Ruskin University and GEANT, is working with academics from Birmingham City University and the University of Central Lancashire to investigate how converting human tissue spectroscopy data into sounds can help to diagnose cancer.

Cancer diagnosis typically involves taking a biopsy, sending it to the lab and waiting for the results.  One of the methodologies to detect cancer is based on spectroscopy, which involves firing a particular light into a small piece of tissue and observing how it reacts.

However, analysing the results and determining healthy cells from cancer cells usually involves the use of complex algorithms and assigning the cell type by eye, which is a time-consuming process.

The recent study by Dr Vicinanza and his colleagues shows how data sonification – where data is conveyed as audio signals as opposed to visual illustrations such as graphs – can improve standard techniques currently used in spectroscopy stem cell analysis.

Dr Vicinanza will be showcasing this research at the European Commission’s ICT (Information and Communication Technologies) conference in Lisbon this week. 

Delegates will be able to listen to the different sounds that data sonification can produce to aid faster cancer diagnosis, and Dr Vicinanza will explain to delegates the difference between the sounds and what they mean.

Dr Vicinanza, Director of Anglia Ruskin’s Sound and Game Engineering (SAGE) research group, said: “Our collaboration is aimed at creating sounds from the spectroscopy results. 

“Advanced synthesis techniques can control the sound parameters using information contained in the data, and so the measurements are practically ‘shaping’ the sound.

“By classifying this data into audio signals, it is easier to differentiate between different types of cell.  This could improve accuracy and allow researchers to search through large volumes of data very quickly.”

 

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For more press information please contact:
Jon Green on t: 01245 68 4717, e: jon.green@anglia.ac.uk
Jamie Forsyth on t: 01245 68 4716, e: jamie.forsyth@anglia.ac.uk
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