Systematic parameter mapping for Wavelet-Based scatter correction in SPECT: clinical perception versus quantitative metrics

BACKGROUND: Photon scatter significantly degrades Single Photon Emission Computed Tomography (SPECT) image quality, with scattered photons accounting for 30-40% of detected counts within standard energy windows. While conventional scatter correction methods face limitations including noise amplification and computational demands, wavelet transforms offer promising capabilities for sinogram-domain correction. However, comprehensive parameter optimization remains unexplored. METHODS: We evaluated 96 mother wavelets across seven families, implementing three decomposition levels and five thresholding strategies in a Monte Carlo simulation framework. Scatter-contaminated sinograms were processed using discrete wavelet transforms and reconstructed via filtered backprojection. Quantitative assessment employed Universal Image Quality Index (UIQI) with varying block sizes (3 × 3, 25 × 25, 128 × 128) and Root Mean Square Error (RMSE). Three nuclear medicine physicians performed blinded qualitative assessment of the processed images. RESULTS: Among 94 viable wavelets (excluding outliers db45 and rbio3.1), global optimization identified Rigrsure and Heursure thresholding at decomposition level 1 as optimal for maximizing UIQI (0.559 ± 0.002), while per-slice optimization favored Minimaxi thresholding at level 2. Strong positive correlation existed between UIQI (25 × 25) and UIQI (128 × 128) (r = 0.887, p < 0.01), with both metrics inversely related to RMSE error (r≈ - 0.73, p < 0.01). Despite UIQI optimization, RMSE-optimized images received significantly higher visual quality rankings from physicians (69% improvement, p < 0.001), revealing critical divergence between quantitative metrics and diagnostic utility. CONCLUSION: This study establishes wavelet-based scatter correction as a viable approach for SPECT image enhancement through systematic parameter mapping. The marked preference for RMSE-optimized images over UIQI-optimized ones underscores the necessity of aligning algorithmic optimization with clinical perception rather than technical metrics alone. These findings provide a foundation for standardizing wavelet implementation in SPECT scatter correction, directly connecting mathematical optimization to diagnostic relevance in nuclear medicine imaging.