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eess.SP2025
Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography
Harshit Agrawal, Ari Hietanen, Simo Särkkä
Purpose: Scatter artifacts drastically degrade the image quality of cone-beam computed tomography (CBCT) scans. Although deep learning-based methods show promise in estimating scat…
eess.SP2024★ 4 cited
Utilizing U-Net Architectures with Auxiliary Information for Scatter Correction in CBCT Across Different Field-of-View Settings
Harshit Agrawal, Ari Hietanen, Simo Särkkä
Cone-beam computed tomography (CBCT) has become a vital imaging technique in various medical fields but scatter artifacts are a major limitation in CBCT scanning. This challenge is…