Automated reference-free detection of motion artifacts in magnetic resonance images

T Küstner, A Liebgott, L Mauch, P Martirosian… - … Resonance Materials in …, 2018 - Springer
Objectives Our objectives were to provide an automated method for spatially resolved
detection and quantification of motion artifacts in MR images of the head and abdomen as …

A machine-learning framework for automatic reference-free quality assessment in MRI

T Küstner, S Gatidis, A Liebgott, M Schwartz… - Magnetic resonance …, 2018 - Elsevier
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large
amount of data is created per examination which needs to be checked for sufficient quality in …

ImFEATbox: a toolbox for extraction and analysis of medical image features

A Liebgott, T Küstner, H Strohmeier, T Hepp… - International journal of …, 2018 - Springer
Purpose In medical imaging, the digital post-processing and analysis of acquired images
has become an important research field. Topics include various applications of image …

Population-based imaging biobanks as source of big data

S Gatidis, SD Heber, C Storz, F Bamberg - La radiologia medica, 2017 - Springer
Advances of computational sciences over the last decades have enabled the introduction of
novel methodological approaches in biomedical research. Acquiring extensive and …

Active learning for magnetic resonance image quality assessment

A Liebgott, T Küstner, S Gatidis… - … on acoustics, speech …, 2016 - ieeexplore.ieee.org
In medical imaging, the acquired images are usually analyzed by a human observer and
rated with respect to a diagnostic question. However, this procedure is time-demanding and …

An easy-to-use image labeling platform for automatic magnetic resonance image quality assessment

T Küstner, P Wolf, M Schwartz… - 2017 IEEE 14th …, 2017 - ieeexplore.ieee.org
In medical imaging, images are usually evaluated by a human observer (HO) depending on
the underlying diagnostic question which can be a time-demanding and cost-intensive …

Evaluation of image quality of MRI data for brain tumor surgery

F Heckel, F Arlt, B Geisler, S Zidowitz… - … Imaging 2016: Image …, 2016 - spiedigitallibrary.org
3D medical images are important components of modern medicine. Their usefulness for the
physician depends on their quality, though. Only high-quality images allow accurate and …

ImFEATbox: An MR image processing toolbox for extracting and analyzing features

A Liebgott, S Gatidis, P Martirosian… - Proceedings of the …, 2017 - archive.ismrm.org
In various image processing applications, finding appropriate mathematical descriptions
which reflect or extract characteristics of the underlying content from acquired MR images is …

Active learning for automated reference-free MR image quality assessment: decreasing the number of required training samples by reduction of intra-batch …

A Liebgott, D Boborzi, S Gatidis, F Schick… - Proceedings of the …, 2018 - archive.ismrm.org
Active learning aims to reduce the amount of labeled data required to adequately train a
classifier by iteratively selecting samples carrying the most valuable information for the …

Reinforcement Learning for Automated Reference-free MR Image Quality Assessment

A Liebgott, J Yi, T Küstner, K Nikolaou, B Yang… - archive.ismrm.org
Reinforcement learning is a method aiming to model a learner similar to human learning
behavior. In this study, we investigate the possibility to utilize this technique to select an …