Publications by authors named "Rouzbeh Maani"

Article Synopsis
  • A study aimed to test whether texture analysis of MRI images can detect cerebral degeneration in patients with amyotrophic lateral sclerosis (ALS), despite traditional MRI scans showing no clear signs of degeneration.
  • High-resolution MRIs were taken from ALS patients and healthy controls, and lower resolutions were created to evaluate how resolution affects the analysis.
  • Results showed that texture analysis could differentiate between ALS patients and healthy individuals at certain resolutions, with optimal accuracy achieved when paired with expert visual assessments, suggesting texture analysis may serve as a valuable tool for identifying neuroimaging biomarkers in ALS.*
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Introduction: Routine MR images do not consistently reveal pathological changes in the brain in ALS. Texture analysis, a method to quantitate voxel intensities and their patterns and interrelationships, can detect changes in images not apparent to the naked eye. Our objective was to evaluate cerebral degeneration in ALS using 3-dimensional texture analysis of MR images of the brain.

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This paper presents a novel voxel-based method for texture analysis of brain images. Texture analysis is a powerful quantitative approach for analyzing voxel intensities and their interrelationships, but has been thus far limited to analyzing regions of interest. The proposed method provides a 3D statistical map comparing texture features on a voxel-by-voxel basis.

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This paper presents a method for robust volumetric texture classification. It also proposes 2D and 3D gradient calculation methods designed to be robust to imaging effects and artifacts. Using the proposed 2D method, the gradient information is extracted on the XYZ orthogonal planes at each voxel and used to form a local coordinate system.

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This paper presents a novel rotation invariant method for texture classification based on local frequency components. The local frequency components are computed by applying 1-D Fourier transform on a neighboring function defined on a circle of radius R at each pixel. We observed that the low frequency components are the major constituents of the circular functions and can effectively represent textures.

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The staggering number of images acquired by modern modalities requires new approaches for medical data transmission. There have been several attempts to improve data transmission time between medical imaging systems. These attempts were mostly based on compression.

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