Christoph Haarburger

发表

Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach

C. Kuhl, P. Bruners, D. Merhof, 2020, European Radiology Experimental.

Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, J. Kather, 2022, ArXiv.

Artificial Intelligence for Clinical Interpretation of Bedside Chest Radiographs.

Jakob Nikolas Kather, J. Kather, P. Bruners, 2022, Radiology.

Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation

Jakob Nikolas Kather, J. Kather, V. Schulz, 2022, Nature Machine Intelligence.

Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks

Dorit Merhof, Nicolas Horst, Christoph Haarburger, 2019, VCBM.

A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, J. Niehues, 2022, Scientific reports.

Diffusion MRI Signal Augmentation: From Single Shell to Multi Shell with Deep Learning

Dorit Merhof, Simon Koppers, Christoph Haarburger, 2016, MICCAI 2016.

Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI.

Dorit Merhof, Christiane Kuhl, Christoph Haarburger, 2019, Radiology.

Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Generation

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, S. Engelhardt, 2022, 2211.03364.

Image prediction of disease progression by style-based manifold extrapolation

Jakob Nikolas Kather, V. Schulz, F. Kiessling, 2021, 2111.11439.

Breaking medical data sharing boundaries by using synthesized radiographs

Volkmar Schulz, Dorit Merhof, Fabian Kiessling, 2020, Science Advances.

Transfer Learning for Breast Cancer Malignancy Classification based on Dynamic Contrast-Enhanced MR Images

Dorit Merhof, Christoph Haarburger, Johannes Thüring, 2018, Bildverarbeitung für die Medizin.

Breaking Medical Data Sharing Boundaries by Employing Artificial Radiographs

Dorit Merhof, Fabian Kiessling, Nicolas Horst, 2019, bioRxiv.

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge

Sergio Escalera, Mitko Veta, Xiahai Zhuang, 2021, IEEE Transactions on Medical Imaging.

Author Correction: Radiomics feature reproducibility under inter-rater variability in segmentations of CT images.

C. Kuhl, D. Merhof, D. Truhn, 2021, Scientific reports.

Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, S. Nebelung, 2022, ArXiv.

Elevating Fundoscopic Evaluation to Expert Level - Automatic Glaucoma Detection Using Data from the Airogs Challenge

Jakob Nikolas Kather, S. Nebelung, D. Truhn, 2022, 2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC).

Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization pdf

Markus Zimmermann, Fabian Kiessling, Christoph Haarburger, 2020, Nature Communications.

Radiomics feature reproducibility under inter-rater variability in segmentations of CT images

Dorit Merhof, Christiane Kuhl, Christoph Haarburger, 2020, Scientific Reports.

Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning pdf

Volkmar Schulz, Fabian Kiessling, Christoph Haarburger, 2021, ArXiv.

Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data

Jakob Nikolas Kather, S. Nebelung, D. Truhn, 2023, Scientific reports.

Radiomic Feature Stability Analysis Based on Probabilistic Segmentations

D. Merhof, D. Truhn, Christoph Haarburger, 2019, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification pdf

Dorit Merhof, Christiane Kuhl, Michael Baumgartner, 2019, MICCAI.

Reliability as a Precondition for Trust—Segmentation Reliability Analysis of Radiomic Features Improves Survival Prediction

S. Nebelung, D. Truhn, Christoph Haarburger, 2022, Diagnostics.

Denoising diffusion probabilistic models for 3D medical image generation

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, S. Engelhardt, 2023, Scientific reports.

A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, J. Niehues, 2023, Scientific reports.

Robustness of Radiomics for Survival Prediction of Brain Tumor Patients Depending on Resection Status

Leon Weninger, Christoph Haarburger, Dorit Merhof, 2019, Front. Comput. Neurosci..

Image-Based Survival Prediction for Lung Cancer Patients Using CNNS

Dorit Merhof, Oliver Rippel, Christoph Haarburger, 2018, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Image-based Survival Analysis for Lung Cancer Patients using CNNs

D. Merhof, Oliver Rippel, Christoph Haarburger, 2018, ArXiv.

Medical Foundation Models are Susceptible to Targeted Misinformation Attacks

Jakob Nikolas Kather, S. Nebelung, D. Truhn, 2023, ArXiv.

Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers.

Jakob Nikolas Kather, S. Nebelung, D. Truhn, 2023, Radiology.