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Impact of Labeling Process on Automated Motion Artifact Detection in Whole-Body MR Images with a Deep Learning Approach: A Comparative Study. Proceedings of the ISMRM Workshop on Machine Learning, 2018. [PUMA: iqa machinelearning myown]
Combined Unsupervised-Supervised Classification of Multiparametric PET/MRI Imaging Data of the Prostate. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Milano, Italy, Mai 2014. [PUMA: MachineLearning kSpaceAstronauts myown]
Combined unsupervised-supervised classification of multiparametric PET/MRI data: Application to prostate cancer. NMR in biomedicine, (28)7:914-22, Juli 2015. [PUMA: MachineLearning kSpaceAstronauts myown] URL
Automated image quality assessment in whole-body MRI. Proceedings of the Radiological Society of North America (RSNA), Chicago, USA, November 2016. [PUMA: IQA MachineLearning kSpaceAstronauts myown]
Active Learning for Magnetic Resonance Image Quality Assessment. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, März 2016. [PUMA: IQA MachineLearning kSpaceAstronauts myown] URL
A new approach for automatic image quality assessment. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, Juni 2015. [PUMA: IQA MachineLearning kSpaceAstronauts myown]
An Active Learning platform for automatic MR image quality assessment. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Singapore, Mai 2016. [PUMA: IQA MachineLearning kSpaceAstronauts myown]
An easy-to-use image labeling platform for automatic Magnetic Resonance Image Quality Assessment. Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, April 2017. [PUMA: IQA MachineLearning kSpaceAstronauts myown]