Rapid development of image analysis research tools: Bridging the gap between researcher and clinician with pyOsiriX

Computers in Biology and Medicine
Matthew D BlackledgeMartin O Leach

Abstract

We present pyOsiriX, a plugin built for the already popular dicom viewer OsiriX that provides users the ability to extend the functionality of OsiriX through simple Python scripts. This approach allows users to integrate the many cutting-edge scientific/image-processing libraries created for Python into a powerful DICOM visualisation package that is intuitive to use and already familiar to many clinical researchers. Using pyOsiriX we hope to bridge the apparent gap between basic imaging scientists and clinical practice in a research setting and thus accelerate the development of advanced clinical image processing. We provide arguments for the use of Python as a robust scripting language for incorporation into larger software solutions, outline the structure of pyOsiriX and how it may be used to extend the functionality of OsiriX, and we provide three case studies that exemplify its utility. For our first case study we use pyOsiriX to provide a tool for smooth histogram display of voxel values within a user-defined region of interest (ROI) in OsiriX. We used a kernel density estimation (KDE) method available in Python using the scikit-learn library, where the total number of lines of Python code required to generate this tool wa...Continue Reading

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Citations

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Methods Mentioned

BETA
X-ray

Software Mentioned

KernelDensity
DicomSeries
osirix
pyOsiriX
DICOM
SciPy
Insight Segmentation and Registration Toolkit ( ITK )
ViewerController
eFilm
VRtool

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