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Peter Neher

Showing results (31-40 of 38) with videos related to

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Investigative Radiology|October 18, 2022
Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter StudyMarkus Wennmann, Peter Neher, Nikolas Stanczyk, et al.
Scientific Reports|October 10, 2025
Automated radiomics model for prediction of therapy response and minimal residual disease from baseline MRI in multiple myelomaFabian Bauer, Marina Hajiyianni, Niels Weinhold, et al.
Nature Communications|September 10, 2024
Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysisMarc Cicero Schubert, Stella Judith Soyka, Amr Tamimi, et al.
Academic Radiology|July 10, 2025
Automated Detection of Focal Bone Marrow Lesions From MRI: A Multi-center Feasibility Study in Patients with Monoclonal Plasma Cell DisordersMarkus Wennmann, Jessica Kächele, Arvin von Salomon, et al.
Investigative Radiology|May 24, 2023
Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and RadiomicsMarkus Wennmann, Wenlong Ming, Fabian Bauer, et al.
Journal of Magnetic Resonance Imaging : JMRI|June 11, 2019
Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challengeVishwesh Nath, Kurt G Schilling, Prasanna Parvathaneni, et al.
Neuroimage|October 15, 2018
Limits to anatomical accuracy of diffusion tractography using modern approachesKurt G Schilling, Vishwesh Nath, Colin Hansen, et al.
JCO Clinical Cancer Informatics|November 9, 2020
Joint Imaging Platform for Federated Clinical Data AnalyticsJonas Scherer, Marco Nolden, Jens Kleesiek, et al.
Pageof 4

Showing results (31-40 of 38) with videos related to

Sort By:
Pageof 4
You have reached the last page of results.This site can display upto 38 results.
Investigative Radiology|October 18, 2022
Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter StudyMarkus Wennmann, Peter Neher, Nikolas Stanczyk, et al.
Scientific Reports|October 10, 2025
Automated radiomics model for prediction of therapy response and minimal residual disease from baseline MRI in multiple myelomaFabian Bauer, Marina Hajiyianni, Niels Weinhold, et al.
Nature Communications|September 10, 2024
Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysisMarc Cicero Schubert, Stella Judith Soyka, Amr Tamimi, et al.
Academic Radiology|July 10, 2025
Automated Detection of Focal Bone Marrow Lesions From MRI: A Multi-center Feasibility Study in Patients with Monoclonal Plasma Cell DisordersMarkus Wennmann, Jessica Kächele, Arvin von Salomon, et al.
Investigative Radiology|May 24, 2023
Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and RadiomicsMarkus Wennmann, Wenlong Ming, Fabian Bauer, et al.
Journal of Magnetic Resonance Imaging : JMRI|June 11, 2019
Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challengeVishwesh Nath, Kurt G Schilling, Prasanna Parvathaneni, et al.
Neuroimage|October 15, 2018
Limits to anatomical accuracy of diffusion tractography using modern approachesKurt G Schilling, Vishwesh Nath, Colin Hansen, et al.
JCO Clinical Cancer Informatics|November 9, 2020
Joint Imaging Platform for Federated Clinical Data AnalyticsJonas Scherer, Marco Nolden, Jens Kleesiek, et al.
Pageof 4