Software for analysing digital pathology images proving its usefulness

In a new study, a program known as Spatially Invariant Vector Quantisation (SIVQ) was able to separate malignancy from background tissue in digital slides of micropapillary urothelial carcinoma, a type of bladder cancer whose features can vary widely from case to case and that presents diagnostic challenges even for experts.
‘Being able to pick out cancer from background tissue is a key test for this type of software tool,’ says U-M informatics fellow Jason Hipp, M.D., Ph.D., who shares lead authorship of the paper with resident Steven Christopher Smith, M.D., Ph.D. ‘This is the type of validation that has to happen before digital pathology tools can be widely used in a clinical setting.’
To test the software