Daniel Truhn
Orcid: 0000-0002-9605-0728
According to our database1,
Daniel Truhn
authored at least 54 papers
between 2007 and 2024.
Collaborative distances:
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Bibliography
2024
Encrypted federated learning for secure decentralized collaboration in cancer image analysis.
Medical Image Anal., February, 2024
IEEE Trans. Medical Imaging, January, 2024
In-context learning enables multimodal large language models to classify cancer pathology images.
CoRR, 2024
Joint multi-task learning improves weakly-supervised biomarker prediction in computational pathology.
CoRR, 2024
An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs.
CoRR, 2024
2023
Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs.
Comput. Methods Programs Biomed., June, 2023
From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology.
CoRR, 2023
From Text to Image: Exploring GPT-4Vision's Potential in Advanced Radiological Analysis across Subspecialties.
CoRR, 2023
A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology.
CoRR, 2023
Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models.
CoRR, 2023
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining.
CoRR, 2023
CoRR, 2023
Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies.
CoRR, 2023
Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images.
CoRR, 2023
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy.
CoRR, 2023
Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation.
CoRR, 2023
MedAlpaca - An Open-Source Collection of Medical Conversational AI Models and Training Data.
CoRR, 2023
Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology.
CoRR, 2023
Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study.
CoRR, 2023
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Proceedings of the Simulation and Synthesis in Medical Imaging, 2023
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
2022
Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation.
Nat. Mac. Intell., November, 2022
Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474.
Medical Image Anal., 2022
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.
Medical Image Anal., 2022
Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis.
CoRR, 2022
Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels.
CoRR, 2022
Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation.
CoRR, 2022
Automated major psoas muscle volumetry in computed tomography using machine learning algorithms.
Int. J. Comput. Assist. Radiol. Surg., 2022
Proceedings of the Eleventh International Conference on Image Processing Theory, 2022
2021
Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning.
CoRR, 2021
An Asymmetric Cycle-Consistency Loss For Dealing With Many-To-One Mappings In Image Translation: A Study On Thigh Mr Scans.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
2020
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization.
CoRR, 2020
An Asymetric Cycle-Consistency Loss for Dealing with Many-to-One Mappings in Image Translation: A Study on Thigh MR Scans.
CoRR, 2020
A Method for Semantic Knee Bone and Cartilage Segmentation with Deep 3D Shape Fitting Using Data from the Osteoarthritis Initiative.
Proceedings of the Shape in Medical Imaging - International Workshop, 2020
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020
2019
Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks.
Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019
2018
Abbreviated breast biopsy procedure by registration of craniocaudal and mediolateral breast MR images.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Transfer Learning for Breast Cancer Malignancy Classification based on Dynamic Contrast-Enhanced MR Images.
Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018
2008
2007
Camera Calibration for Fish-Eye Lenses en Endoscopy with an Application to 3d Reconstruction.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007