48 citations · 70 across the 5 of their papers we have counts for
5 papers
Towards AI Lesion Tracking in PET/CT Imaging: A Siamese-based CNN Pipeline applied on PSMA PET/CT Scans
Stefan P. Hein, Manuel Schultheiss, Andrei Gafita +7
Assessing tumor response to systemic therapies is one of the main applications of PET/CT. Routinely, only a small subset of index lesions out of multiple lesions is analyzed. Howev…
Improving Automated Hemorrhage Detection in Sparse-view Computed Tomography via Deep Convolutional Neural Network based Artifact Reduction
Johannes Thalhammer, Manuel Schultheiss, Tina Dorosti +4
This is a preprint. The latest version has been published here: https://pubs.rsna.org/doi/10.1148/ryai.230275 Purpose: Sparse-view computed tomography (CT) is an effective way to r…
Optimizing Convolutional Neural Networks for Chronic Obstructive Pulmonary Disease Detection in Clinical Computed Tomography Imaging
Tina Dorosti, Manuel Schultheiss, Felix Hofmann +7
We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD) based on emphysema presence in the lung with convolutional neural networks (CNN) by explorin…
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…
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…