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Texture quantification of medical images using a novel complex space-frequency transform

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Objective

To develop an efficient space-frequency transform for texture analysis and demonstrate its application on magnetic resonance (MR) images of multiple sclerosis (MS) patients.

Materials and methods

We applied our new transform to MR images of three enhancing lesions from two relapsing-remitting MS patients acquired serially over 9 months. Local spectra of the images were generated using our new technique, and spatial frequencies corresponding to MS lesion activity were extracted by applying a band-pass filter and inverting. We examined the changes in T2 intensity and low-frequency energy (LFE) over time within the lesion, surrounding tissue and a region of normal-appearing white matter (NAWM).

Results

We calculated complex local spectra of 428 × 428 images in approximately 1 min and achieved a spatial frequency resolution of 0.05 cm−1. We observed an increase in LFE within the lesion and a drop in LFE in the hyperintense border of tissue surrounding the lesion.

Conclusion

We have developed an efficient, invertible transform that produces high-resolution local frequency spectra of an MR image in approximately 1 min. Negative LFE values in the boundaries of an active lesion may help discriminate between the core lesion undergoing demyelination and a border of inflammation.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Calgary, 2500 University Dr NW, Calgary, AB, Canada, T2N 1N4

    Sylvia Drabycz

  2. Departments of Radiology and Clinical Neurosciences, University of Calgary, 2500 University Dr NW, Calgary, AB, Canada, T2N 1N4

    J. Ross Mitchell

Authors
  1. Sylvia Drabycz
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  2. J. Ross Mitchell
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Corresponding author

Correspondence to J. Ross Mitchell.

Additional information

This work was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Alberta Heritage Foundation for Medical Research (AHFMR). The authors would like to acknowledge the support of the Alberta Informatics Circle of Research Excellece (iCORE).

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Drabycz, S., Mitchell, J.R. Texture quantification of medical images using a novel complex space-frequency transform. Int J CARS 3, 465–475 (2008). https://doi.org/10.1007/s11548-008-0219-4

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  • DOI: https://doi.org/10.1007/s11548-008-0219-4

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