Evaluation of Machine Learning Reconstruction Techniques for Accelerated Brain MRI Scans

Figure 3: Distribution of Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR), and Haar wavelet-based Perceptual Similarity Index (HaarPSI) scores for DeepFoqus-Accelerate reconstructions: (a-c) show results across 408 samples at 2x, 3x, and 4x acceleration, and (d-f) present distributions for the 36 image sets evaluated by reviewers. Figure 4: (A-B) Representative standard-of-care (SOC) images (first row) and DeepFoqus-Accelerate reconstructions from accelerated scans (second row), with corresponding quantitative and qualitative scores presented in the third row. Panel (B) shows two slices of the worst-case scenario in the qualitative dataset, characterized by wrap-around and motion artifacts. Discussion This evaluation of DeepFoqus-Accelerate demonstrates that this FDA-cleared k-space-based DL reconstruction software can reliably enable up to fourfold accelerated brain MRI acquisition without compromising diagnostic image quality. Both expert review and quantitative image similarity metrics confirm that AI-reconstructed images are clinically equivalent to fully sampled standards.