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

Sylvia Drabycz, J. Ross Mitchell

Research output: Contribution to journalArticle

6 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)465-475
Number of pages11
JournalInternational Journal of Computer Assisted Radiology and Surgery
Volume3
Issue number5
DOIs
StatePublished - Jan 1 2008

Keywords

  • Computer-assisted image interpretation
  • Fourier analysis
  • Magnetic resonance imaging
  • Multiple sclerosis

ASJC Scopus subject areas

  • Surgery
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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