Myocardial Perfusion Single-Photon Emission Computed Tomography (SPECT) Image Denoising: A Comparative Study

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Image Processing

Background:

• Myocardial perfusion single-photon emission computed tomography (SPECT) is crucial for diagnosing heart conditions.
• Image quality in SPECT can be compromised by noise, potentially affecting diagnostic accuracy.
• Various digital filters are available for image noise reduction.

Purpose of the Study:

• To evaluate the effectiveness of different filters in enhancing myocardial perfusion SPECT image quality.
• To compare the performance of Butterworth, Hamming, Gaussian, Wiener, and median-modified Wiener filters.
• To identify the optimal filter and kernel size for denoising myocardial perfusion SPECT images.

Main Methods:

• SPECT images were acquired using a Siemens Symbia T2 dual-head SPECT/CT scanner.
• Over 900 images from 30 patients were analyzed.
• Filters (Butterworth, Hamming, Gaussian, Wiener, median-modified Wiener) with varying kernel sizes were applied.
• Image quality was assessed using signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and contrast-to-noise ratio (CNR).

Main Results:

• The Wiener filter with a 5 × 5 kernel size yielded the highest SNR and CNR.
• The Gaussian filter achieved the highest PSNR.
• The Wiener filter (5 × 5 kernel) demonstrated superior denoising performance compared to other tested filters.

Conclusions:

• The Wiener filter, particularly with a 5 × 5 kernel, is highly effective for improving myocardial perfusion SPECT image quality.
• This study provides a comprehensive comparison of filters for SPECT image denoising.
• The findings offer valuable insights for optimizing image acquisition and processing protocols in myocardial perfusion SPECT.