F. Khader

发表

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.

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.

Encrypted federated learning for secure decentralized collaboration in cancer image analysis

Jakob Nikolas Kather, J. Chang-Claude, M. Hoffmeister, 2022, medRxiv.

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology

Ming Y. Lu, Jakob Nikolas Kather, T. Brinker, 2022, Medical Image Anal..

Swarm learning for decentralized artificial intelligence in cancer histopathology

Jakob Nikolas Kather, T. Brinker, T. Luedde, 2021, Nature Medicine.

Benchmarking artificial intelligence methods for end-to-end computational pathology

Ming Y. Lu, Jakob Nikolas Kather, T. Brinker, 2021, bioRxiv.

Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels

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

Collaborative training of medical artificial intelligence models with non-uniform labels

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, S. Nebelung, 2022, Scientific reports.

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

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

Swarm learning for decentralized artificial intelligence in cancer histopathology

Jakob Nikolas Kather, T. Brinker, T. Luedde, 2021, Nature Network Boston.

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.

AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge

Coen de Vente, Hyun Bin Cho, B. Ginneken, 2023, IEEE transactions on medical imaging.

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).

Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers

Jakob Nikolas Kather, S. Nebelung, D. Truhn, 2023, MLMI@MICCAI.

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.

Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images.

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

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

S. Nebelung, D. Truhn, Firas Khader, 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.

Fast, Accurate, and Robust T2 Mapping of Articular Cartilage by Neural Networks

A. Prescher, S. Nebelung, D. Truhn, 2022, Diagnostics.

Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection

Jakob Nikolas Kather, Soroosh Tayebi Arasteh, S. Nebelung, 2023, 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI).

Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs

S. Nebelung, D. Truhn, J. Stegmaier, 2023, ArXiv.

Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474

Ming Y. Lu, Jakob Nikolas Kather, T. Brinker, 2022, Medical Image Anal..

Fibroglandular tissue segmentation in breast MRI using vision transformers: a multi-institutional evaluation

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

Medical Foundation Models are Susceptible to Targeted Misinformation Attacks

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

Generating Synthetic Computed Tomography for Radiotherapy: SynthRAD2023 Challenge Report

Z. Perkó, Ze-xiang Chen, J. Dafflon, 2024, 2403.08447.

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

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