Three-dimensional distortion model for magnetic resonance images

Larry A. DeSoto; David R. Haynor; Yongmin Kim

doi:10.1117/12.59487

1 May 1992 Three-dimensional distortion model for magnetic resonance images

Larry A. DeSoto, David R. Haynor, Yongmin Kim

Proceedings Volume 1653, Medical Imaging VI: Image Capture, Formatting, and Display; (1992) https://doi.org/10.1117/12.59487
Event: Medical Imaging VI, 1992, Newport Beach, CA, United States

Abstract

Magnetic resonance imaging (MRI) has progressed rapidly within the last decade. In addition to better soft tissue discrimination than CT, MRI is capable of imaging a volume in multiple planes. If these planes can be accurately registered, it is possible to create a 3-D image database. This 3-D database can then be used to generate considerably more accurate target coordinates for use in applications such as stereotaxic neurosurgery or radiation oncology where precise measurements are required. Despite these advantages, use of MRI in these applications has been limited because of fundamental questions about the geometric accuracy of the images. Distortion in MR images is inevitable because of nonlinearities and inhomogeneities in the magnetic gradient fields that are used for spatial encoding of the signal. We have developed a model for this distortion which has allowed us to minimize the localization errors using MR images and to improve the geometric correspondence between images acquired in different planes. A special phantom is imaged and analyzed to determine machine dependent parameters for the distortion model. These parameters may then be applied to the geometric correction of patient images, which are acquired separately. The model has been incorporated into an integrated stereotaxic planning system designed for interactive use in the operating room. In this paper, we present details of the model and experimental results.

Citation Download Citation

Larry A. DeSoto, David R. Haynor, and Yongmin Kim "Three-dimensional distortion model for magnetic resonance images", Proc. SPIE 1653, Medical Imaging VI: Image Capture, Formatting, and Display, (1 May 1992); https://doi.org/10.1117/12.59487

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