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Radiology. Artificial Intelligence|May 8, 2024
Improving Automated Hemorrhage Detection at Sparse-View CT via U-Net-based Artifact ReductionJohannes Thalhammer, Manuel Schultheiß, Tina Dorosti, et al.European Journal of Radiology|March 10, 2026
Multiple linear regression models for individualized radiation exposure planning in dark-field chest radiographyHenriette Bast, Tina Dorosti, Maximilian E Lochschmidt, et al.Medical Physics|April 3, 2026
Beam-hardening correction in clinical x-ray dark-field chest radiography using deep-learning-based bone segmentationLennard Kaster, Maximilian E Lochschmidt, Anne M Bauer, et al.Computers in Biology and Medicine|December 20, 2024
Optimizing convolutional neural networks for Chronic Obstructive Pulmonary Disease detection in clinical computed tomography imagingTina Dorosti, Manuel Schultheiss, Felix Hofmann, et al.European Radiology Experimental|May 2, 2024
Improving image quality of sparse-view lung tumor CT images with U-NetAnnika Ries, Tina Dorosti, Johannes Thalhammer, et al.Journal of Imaging Informatics in Medicine|August 27, 2025
Ultra-Low-Dose CTPA Using Sparse Sampling CT Combined with the U-Net for Deep Learning-Based Artifact Reduction: An Exploratory StudyAndreas Philipp Sauter, Johannes Thalhammer, Felix Meurer, et al.Radiology. Artificial Intelligence|May 28, 2025
Estimating Total Lung Volume from Pixel-Level Thickness Maps of Chest Radiographs Using Deep LearningTina Dorosti, Manuel Schultheiß, Philipp Schmette, et al.Pageof 1