Geometric distortion in magnetic resonance imaging systems assessed using an open-source plugin for scientific image...

Area of Science:

• Medical Imaging
• Image Analysis
• Radiology

Background:

• Magnetic resonance (MR) imaging is crucial for delineating tumor locations.
• Geometric distortions in MR images present challenges for accurate treatment planning.
• Uncorrected geometric errors can impact clinical outcomes.

Purpose of the Study:

• To quantitatively assess uncorrectable geometric error, termed residual error (RE), in MR imaging.
• To evaluate the efficacy of an open-source plugin for scientific image analysis in measuring RE.
• To compare the performance of the open-source plugin against commercially available software.

Main Methods:

• Utilized Fiji, an open-source image processing software enhanced by ImageJ.
• Calculated residual error (RE) values using the developed open-source plugin.
• Compared the plugin's RE measurements with those from commercial software.

Main Results:

• The open-source plugin demonstrated accurate quantification of residual error (RE).
• Results from the open-source plugin showed strong agreement with commercially available software.
• The study confirmed the plugin's effectiveness in evaluating MR imaging system distortions.

Conclusions:

• An open-source plugin provides an accurate and effective method for evaluating residual error in MR imaging.
• Quantifying geometric distortion data is essential for safe and precise cancer treatment.
• Consistent evaluation of MR imaging systems can improve treatment accuracy across different facilities and devices.