Publications by authors named "Michael Perkuhn"

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AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.
Fanyang Meng, Jonathan Kottlors, Rahil Shahzad, Haifeng Liu, Philipp Fervers, Michael Perkuhn

Eur Radiol· June 2023

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Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.
Lenhard Pennig, Ulrike Cornelia Isabel Hoyer, Alexandra Krauskopf, Rahil Shahzad, Stephanie T Jünger, Michael Perkuhn

Neuroradiology· December 2021

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Fully Automated MR Detection and Segmentation of Brain Metastases in Non-small Cell Lung Cancer Using Deep Learning.
Stephanie T Jünger, Ulrike Cornelia Isabel Hoyer, Diana Schaufler, Kai Roman Laukamp, Lukas Goertz, Michael Perkuhn

J Magn Reson Imaging· November 2021

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Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT.
Kan He, Xiaoming Liu, Rahil Shahzad, Robert Reimer, Frank Thiele, Michael Perkuhn

Front Oncol· July 2021

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Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.
Kai Roman Laukamp, Lenhard Pennig, Frank Thiele, Robert Reimer, Lukas Görtz, Michael Perkuhn

Clin Neuroradiol· June 2021

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Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning.
Lenhard Pennig, Ulrike Cornelia Isabel Hoyer, Lukas Goertz, Rahil Shahzad, Thorsten Persigehl, Michael Perkuhn

J Magn Reson Imaging· January 2021

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Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning.
Rahil Shahzad, Lenhard Pennig, Lukas Goertz, Frank Thiele, Christoph Kabbasch, Michael Perkuhn

Sci Rep· December 2020

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Comparison of Accuracy of Arrival-Time-Insensitive and Arrival-Time-Sensitive CTP Algorithms for Prediction of Infarct Tissue Volumes.
Lenhard Pennig, Frank Thiele, Lukas Goertz, Kai Roman Laukamp, Michael Perkuhn

Sci Rep· June 2020

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Accuracy of Radiomics-Based Feature Analysis on Multiparametric Magnetic Resonance Images for Noninvasive Meningioma Grading.
Kai Roman Laukamp, Georgy Shakirin, Bettina Baeßler, Frank Thiele, David Zopfs, Michael Perkuhn

World Neurosurg· December 2019

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Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI.
Kai Roman Laukamp, Frank Thiele, Georgy Shakirin, David Zopfs, Andrea Faymonville, Michael Perkuhn

Eur Radiol· January 2019

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Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine.
Michael Perkuhn, Pantelis Stavrinou, Frank Thiele, Georgy Shakirin, Manoj Mohan

Invest Radiol· November 2018

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A Digital Preclinical PET/MRI Insert and Initial Results.
Bjoern Weissler, Pierre Gebhardt, Peter M Dueppenbecker, Jakob Wehner, David Schug, Michael Perkuhn

IEEE Trans Med Imaging· November 2015

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Diffusion-weighted MRI does not reflect kidney fibrosis in a rat model of fibrosis.
Peter Boor, Michael Perkuhn, Martin Weibrecht, Stephanie Zok, Ina V Martin

J Magn Reson Imaging· October 2015

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MR compatibility aspects of a silicon photomultiplier-based PET/RF insert with integrated digitisation.
Bjoern Weissler, Pierre Gebhardt, Christoph W Lerche, Jakob Wehner, Torsten Solf, Michael Perkuhn

Phys Med Biol· September 2014

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Intraindividual quantitative and qualitative comparison of gadopentetate dimeglumine and gadobutrol in time-resolved contrast-enhanced 4-dimensional magnetic resonance angiography in minipigs.
Dariusch Reza Hadizadeh, Gregor Jost, Hubertus Pietsch, Martin Weibrecht, Michael Perkuhn

Invest Radiol· July 2014

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