Open source tool widens image processing window

Radiologists working with large and complex images can now turn to ImageJ, an open source software application for Java-written image processing, to both automate image processing and produce highly reproducible results.

The emergence of new radiological applications and rapidly advancing image processing techniques has led to demand for customized, flexible image analysis software.

"Many existing image processing tools are relatively expensive, proprietary in nature, inflexible, or need images in formats that discard information from the DICOM header," said Dr. Daniel P. Barboriak, a neuroradiologist at Duke University Medical Center.

Barboriak describes how image analyses can be performed directly on DICOM images using a free, Java-based package called ImageJ. Barboriak's study was published online in the April edition of the Journal of Digital Imaging.

The open source ImageJ runs on Windows, Macintosh, or Unix platforms and can read several image formats, including raw and DICOM formats, so radiology users can directly access DICOM images rather than forcing a conversion to a more compatible format.

Users can also automate image analysis using the ImageJ macro language.

"As a general rule, the more automated the analysis and the fewer hands involved, the more reproducible the results," Barboriak said. "Automation means that one can easily write software that adjusts the analysis based on information in the DICOM header."

According to Barboriak, one of the biggest advantages is that ImageJ is a rapidly evolving open source tool, with new plug-ins that perform specific image processing tasks being developed continually. An active ImageJ user group allows for rapid dissemination of image processing advances.

"One huge advantage is that users are not just radiologists but also microscopists, pathologists, and astronomers," he said. "Each specialty has its own image processing problems, so solutions in one field can be helpful in others."

Barboriak's lab at Duke uses ImageJ to analyze T1-weighted MR perfusion imaging and diffusion tensor images on PCs using plug-ins, rather than proprietary software provided by MR manufacturers. The lab uses a plug-in to anonymize images, in addition to using macro scripts to scan images obtained in its MR research protocol.

"If a technologist has entered the wrong pulse sequence or scan parameters, the macro lets us know," he said.

These applications are most appropriate for use in a research setting, according to Barboriak. Software applications used for diagnostic purposes in a clinical setting are considered medical devices and are generally subject to regulatory approval.