May the open source be with you

Open source software in imaging informatics is a natural extension of peer review and could pave the way to better standards implementations, according to researchers at the Mayo Clinic in Rochester, MN.

The open source as peer review model would offer open source implementations of important informatics standards and initiatives (such as DICOM, HL7, and IHE), as well as relevant algorithms (J Am Coll Radiol 2005;2(11)).

Medicine in general, and radiology in particular, continue to struggle with the open source software issue.

"By having source code open to review, it increases understanding for all, improves the quality of implementation, and serves as a benchmark when new standards or methods are proposed," said Dr. Bradley J. Erickson, an associate professor of radiology at Mayo.

Erickson disputes the view of open source as a way to replace vendor products with free products. He considers the primary role of open source as both promoting standards and understanding standards.

"Vendors should be supportive of open source implementations of important standards," Erickson said.

The role of a vendor is to either take the open source implementation and make it into a product or, if they develop a product totally independent of the open source version, test against the open source version to assure adherence to the standard, he said.

Some vendors are understandably reluctant. Companies such as Redhat or MySQL AB have disrupted the traditional software market by adopting a business model of servicing an open source product. This approach is dramatically different from the traditional medical model of a large capital purchase accompanied by a service contract.

Any dramatic change is inherently risky, and established businesses prefer to avoid risk, although there are open source licenses that can protect the commercial value of software, Erickson said.

The finger also points at academia, where good scientific papers have enough detail that experiments can be reproduced as described, according to Erickson.

"Today with software, that means either extremely long papers or that algorithms described should be made available in open source form," he said.

The National Library of Medicine has attempted to address this problem by supporting a library of important image processing algorithms known as the Insight Segmentation and Registration Toolkit.

The National Cancer Institute is taking the same approach. Data developed with grant money will be made public after principal investigators have had the opportunity to publish results.

"Openness is key to improving science and healthcare," Erickson said.