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99m-Tc TRODAT Single-Photon Emission Computerized Tomography Scan Image Compression using Singular Value

Jagrati Chaudhary1, Anil Kumar Pandey1, Angel Hemrom1

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Summary

Singular Value Decomposition (SVD) successfully compressed 99m-Tc TRODAT SPECT images by up to 54.61%, maintaining image quality and clinical accuracy for nuclear medicine applications.

Keywords:
Image compressionTRODAT single-photon emission computerized tomography studysingular value decomposition

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Area of Science:

  • Medical Imaging
  • Signal Processing
  • Nuclear Medicine

Background:

  • 99m-Tc TRODAT SPECT imaging is crucial for diagnosing neurological conditions.
  • Image compression techniques can reduce storage and transmission burdens.
  • Singular Value Decomposition (SVD) is a potential method for image compression.

Purpose of the Study:

  • To compress 99m-Tc TRODAT SPECT images using SVD.
  • To evaluate the compression factor and image quality of compressed SPECT images.
  • To assess the impact of compression on TRODAT uptake measurements.

Main Methods:

  • Computed SVD for 2256 SPECT images from 48 studies.
  • Truncated singular values to reconstruct compressed images.
  • Assessed image quality using visual comparison and objective metrics (Error, SSIM, brightness, GCF, CPP, blur).
  • Compared TRODAT uptake in the basal ganglia between original and compressed images.

Main Results:

  • Achieved up to 54.61% compression with acceptable image quality, deemed identical to originals by physicians.
  • Compressed images showed reduced noise, improved brightness, and sharpness.
  • Median error was 0.0006 and SSIM was 0.93, indicating high similarity.
  • TRODAT uptake differences were negligible in 39/48 studies (max 13% in others).

Conclusions:

  • SVD provides effective compression for 99m-Tc TRODAT SPECT images.
  • Compression up to 54.61% is feasible without compromising diagnostic information.
  • SVD is a viable technique for efficient SPECT image management.