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Nanna Maria Sijtsema
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2020 – today
- 2024
- [j3]Erfan Darzi, Yiqing Shen, Yangming Ou, Nanna Maria Sijtsema, Peter M. A. van Ooijen:
Tackling heterogeneity in medical federated learning via aligning vision transformers. Artif. Intell. Medicine 155: 102936 (2024) - [j2]Alessia De Biase, Liv Ziegfeld, Nanna Maria Sijtsema, Roel Steenbakkers, Robin Wijsman, Lisanne van Dijk, Johannes A. Langendijk, Fokie Cnossen, Peter M. A. van Ooijen:
Probability maps for deep learning-based head and neck tumor segmentation: Graphical User Interface design and test. Comput. Biol. Medicine 177: 108675 (2024) - [j1]Alessia De Biase, Baoqiang Ma, Jiapan Guo, Lisanne van Dijk, Johannes A. Langendijk, Stefan Both, Peter M. A. van Ooijen, Nanna Maria Sijtsema:
Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer. Comput. Methods Programs Biomed. 244: 107939 (2024) - 2023
- [c5]Baoqiang Ma, Jiapan Guo, Lisanne van Dijk, Peter M. A. van Ooijen, Stefan Both, Nanna Maria Sijtsema:
TransRP: Transformer-based PET/CT feature extraction incorporating clinical data for recurrence-free survival prediction in oropharyngeal cancer. MIDL 2023: 1640-1654 - [i6]Erfan Darzidehkalani, Nanna Maria Sijtsema, Peter M. A. van Ooijen:
A Comparative Study of Federated Learning Models for COVID-19 Detection. CoRR abs/2303.16141 (2023) - [i5]Erfan Darzi, Florian Dubost, Nanna Maria Sijtsema, Peter M. A. van Ooijen:
Exploring adversarial attacks in federated learning for medical imaging. CoRR abs/2310.06227 (2023) - [i4]Erfan Darzi, Nanna Maria Sijtsema, Peter M. A. van Ooijen:
Fed-Safe: Securing Federated Learning in Healthcare Against Adversarial Attacks. CoRR abs/2310.08681 (2023) - [i3]Erfan Darzi, Yiqing Shen, Nanna Maria Sijtsema, Peter M. A. van Ooijen:
Tackling Heterogeneity in Medical Federated learning via Vision Transformers. CoRR abs/2310.09444 (2023) - [i2]Erfan Darzi, Florian Dubost, Nanna Maria Sijtsema, Peter M. A. van Ooijen:
The Hidden Adversarial Vulnerabilities of Medical Federated Learning. CoRR abs/2310.13893 (2023) - 2022
- [c4]Hung Chu, Luis Ricardo De la O. Arévalo, Wei Tang, Baoqiang Ma, Yan Li, Alessia De Biase, Stefan Both, Johannes A. Langendijk, Peter M. A. van Ooijen, Nanna Maria Sijtsema, Lisanne van Dijk:
Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging: A Transfer Learning Approach. HECKTOR@MICCAI 2022: 114-120 - [c3]Baoqiang Ma, Yan Li, Hung Chu, Wei Tang, Luis Ricardo De la O. Arévalo, Jiapan Guo, Peter M. A. van Ooijen, Stefan Both, Johannes A. Langendijk, Lisanne van Dijk, Nanna Maria Sijtsema:
Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients. HECKTOR@MICCAI 2022: 240-254 - [i1]Alessia De Biase, Nanna Maria Sijtsema, Lisanne van Dijk, Johannes A. Langendijk, Peter M. A. van Ooijen:
Slice-by-slice deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for spatial uncertainty on FDG PET and CT images. CoRR abs/2207.01623 (2022) - 2021
- [c2]Alessia De Biase, Wei Tang, Nikos Sourlos, Baoqiang Ma, Jiapan Guo, Nanna Maria Sijtsema, Peter M. A. van Ooijen:
Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images. HECKTOR@MICCAI 2021: 109-120 - [c1]Baoqiang Ma, Jiapan Guo, Alessia De Biase, Nikos Sourlos, Wei Tang, Peter M. A. van Ooijen, Stefan Both, Nanna Maria Sijtsema:
Self-supervised Multi-modality Image Feature Extraction for the Progression Free Survival Prediction in Head and Neck Cancer. HECKTOR@MICCAI 2021: 308-317
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