Case study

Image Quality & MTF Analysis

A computational analysis of image quality in medical imaging systems using Modulation Transfer Function (MTF) methodology. The project evaluates how key acquisition parameters — voxel size, filter type, and projection count — affect spatial resolution and contrast preservation in reconstructed images, using both line pair and edge response phantoms.

RoleSignal processing, data analysis, scientific computing
TimelineUniversity project — ENGG4040
FocusMedical Imaging + Signal Processing
MTF analysisSpatial resolution assessmentMedical imaging evaluation
Medical imaging / signal processingDomain
MTF · edge response · line pair phantomsMethods

The brief

Challenge

Quantify spatial resolution in medical imaging systems using only raw measurement data, without direct access to the imaging hardware.

Approach

What we made

Applied Modulation Transfer Function methodology with slanted-edge and line pair phantoms, computing MTF curves from CSV measurement profiles and systematically varying acquisition parameters to isolate each variable's effect.

  • Computed MTF curves from slanted-edge and line pair phantoms to quantify spatial resolution.
  • Evaluated the effect of voxel size, filtering parameters, and projection count on image quality.
  • Applied both 2D and CT imaging analysis frameworks.

Outcome

Results

Produced MTF curves and resolution metrics demonstrating measurable trade-offs between voxel size, filtering, and projection count in reconstructed medical images.

PythonCSVExcelNumPyMatplotlib

Gallery

Visual snapshots

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