06/21/2024
New Publication Alert! Our latest paper, “Texture-preserving low dose CT image denoising using Pearson divergence” introduces a novel approach to enhance texture in low-dose CT images. Previous methods using MSE often had over-smoothed edges and degradation of texture in images, but our proposed Pearson divergence loss mitigates this issue, leading to improved texture preservation. Our results offer clinicians and researchers high-quality CT images crucial for accurate diagnoses and AI model development.
Read more about our findings here:
