New technique to aid bladder cancer diagnosis27 September 2017

Researchers at the ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP) have developed a new and innovative automated computer technique that is able to significantly aid in the diagnosis of bladder cancer.

Lead researcher, Dr Martin Gosnell at CNBP, and colleague, Professor Ewa Goldys, have created an automated image analysis technique that can identify tissue and lesions as either high-risk or minimal-risk. The technique allows suspect lesion images to be quickly and effectively analysed and then classified for cancer risk.

“What we’ve done is develop a computer program to carry out an automated analysis of cystoscopy images,” explained Dr Gosnell. Cystoscopy is one of the most reliable methods for diagnosing bladder cancer.

“Images are taken of the bladder and its insides for suspicious lesions during a routine clinical patient evaluation. Dependent on the findings, this initial scan can then be followed up by a referral to a more experienced urologist, and a biopsy of the suspicious tissue can be undertaken.”

The innovative computerised method mimics diagnostic capability, achieved through a specialised colour segmentation process where the specific colour, luminance and texture of each piece of tissue under examination is able to be analysed, right down to a pixel level. 

The automated diagnostic system has the potential to effectively assist doctors and nurses in their assessment of cystoscopy imagery, reduce the number of erroneous assessments or unnecessary bladder biopsies in the future, and increase cancer clinic efficiency. 

Media issued by the ARC Centre of Excellence for Nanoscale BioPhotonics.

 

Image: Dr Martin Gosnell and Professor Ewa Goldys. 
Image credit: 
www.cnbp.org.au.

Original Published Date: 
Wednesday, September 27, 2017