Daniela Pfeiffer

Orcid: 0000-0003-2002-8337

According to our database1, Daniela Pfeiffer authored at least 13 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

2018
2019
2020
2021
2022
2023
2024
2025
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Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Optimizing convolutional neural networks for Chronic Obstructive Pulmonary Disease detection in clinical computed tomography imaging.
Comput. Biol. Medicine, 2025

2024
Correction for Mechanical Inaccuracies in a Scanning Talbot-Lau Interferometer.
IEEE Trans. Medical Imaging, January, 2024

2023
WNet: A Data-Driven Dual-Domain Denoising Model for Sparse-View Computed Tomography With a Trainable Reconstruction Layer.
IEEE Trans. Computational Imaging, 2023

Improving Image Quality of Sparse-view Lung Cancer CT Images with a Convolutional Neural Network.
CoRR, 2023

Improving Automated Hemorrhage Detection in Sparse-view Computed Tomography via Deep Convolutional Neural Network based Artifact Reduction.
CoRR, 2023

2022
Correction of Motion Artifacts in Dark-Field Radiography of the Human Chest.
IEEE Trans. Medical Imaging, 2022

Iodine Images in Dual-energy CT: Detection of Hepatic Steatosis by Quantitative Iodine Concentration Values.
J. Digit. Imaging, 2022

2021
Direct Differentiation of Pathological Changes in the Human Lung Parenchyma With Grating-Based Spectral X-ray Dark-Field Radiography.
IEEE Trans. Medical Imaging, 2021

Per-Pixel Lung Thickness and Lung Capacity Estimation on Chest X-Rays using Convolutional Neural Networks.
CoRR, 2021

2020
Revealing the Microscopic Structure of Human Renal Cell Carcinoma in Three Dimensions.
IEEE Trans. Medical Imaging, 2020

2019
Dynamic In Vivo Chest X-ray Dark-Field Imaging in Mice.
IEEE Trans. Medical Imaging, 2019

Evaluation of a shortened cardiac MRI protocol for left ventricular examinations: diagnostic performance of T1-mapping and myocardial function analysis.
BMC Medical Imaging, 2019

2018
Evaluation of a machine learning based model observer for x-ray CT.
Proceedings of the Medical Imaging 2018: Image Perception, 2018


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