most citedWNet: A data-driven dual-domain denoising model for sparse-view computed tomography with a trainable reconstruction layer

48 citations · 51 across the 2 of their papers we have counts for

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eess.IV2022★ 48 cited

WNet: A data-driven dual-domain denoising model for sparse-view computed tomography with a trainable reconstruction layer

Theodor Cheslerean-Boghiu, Felix C. Hofmann, Manuel Schultheiß +3

Deep learning based solutions are being succesfully implemented for a wide variety of applications. Most notably, clinical use-cases have gained an increased interest and have been…

eess.IV2021★ 3 cited

Estimating Total Lung Volume from Pixel-level Thickness Maps of Chest Radiographs Using Deep Learning

Tina Dorosti, Manuel Schultheiss, Philipp Schmette +11

Purpose: To estimate the total lung volume (TLV) from real and synthetic frontal chest radiographs (CXR) on a pixel level using lung thickness maps generated by a U-Net deep learni…