Nanna Maria Sijtsema

According to our database, Nanna Maria Sijtsema authored at least 14 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer.

Alessia De Biase, Baoqiang Ma, Jiapan Guo, Lisanne van Dijk, Johannes A. Langendijk, Stefan Both, Peter M. A. van Ooijen, Nanna Maria Sijtsema

Comput. Methods Programs Biomed., 2024

Probability maps for deep learning-based head and neck tumor segmentation: Graphical User Interface design and test.

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

Comput. Biol. Medicine, 2024

Tackling heterogeneity in medical federated learning via aligning vision transformers.

Erfan Darzi, Yiqing Shen, Yangming Ou, Nanna Maria Sijtsema, Peter M. A. van Ooijen

Artif. Intell. Medicine, 2024

2023

The Hidden Adversarial Vulnerabilities of Medical Federated Learning.

Erfan Darzi, Florian Dubost, Nanna Maria Sijtsema, Peter M. A. van Ooijen

CoRR, 2023

Tackling Heterogeneity in Medical Federated learning via Vision Transformers.

Erfan Darzi, Yiqing Shen, Nanna Maria Sijtsema, Peter M. A. van Ooijen

CoRR, 2023

Fed-Safe: Securing Federated Learning in Healthcare Against Adversarial Attacks.

Erfan Darzi, Nanna Maria Sijtsema, Peter M. A. van Ooijen

CoRR, 2023

Exploring adversarial attacks in federated learning for medical imaging.

Erfan Darzi, Florian Dubost, Nanna Maria Sijtsema, Peter M. A. van Ooijen

CoRR, 2023

A Comparative Study of Federated Learning Models for COVID-19 Detection.

Erfan Darzidehkalani, Nanna Maria Sijtsema, Peter M. A. van Ooijen

CoRR, 2023

TransRP: Transformer-based PET/CT feature extraction incorporating clinical data for recurrence-free survival prediction in oropharyngeal cancer.

Baoqiang Ma, Jiapan Guo, Lisanne van Dijk, Peter M. A. van Ooijen, Stefan Both, Nanna Maria Sijtsema

Proceedings of the Medical Imaging with Deep Learning, 2023

2022

Slice-by-slice deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for spatial uncertainty on FDG PET and CT images.

Alessia De Biase, Nanna Maria Sijtsema, Lisanne van Dijk, Johannes A. Langendijk, Peter M. A. van Ooijen

CoRR, 2022

Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients.

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

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022

Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging: A Transfer Learning Approach.

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

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022

2021

Self-supervised Multi-modality Image Feature Extraction for the Progression Free Survival Prediction in Head and Neck Cancer.

Baoqiang Ma, Jiapan Guo, Alessia De Biase, Nikos Sourlos, Wei Tang, Peter M. A. van Ooijen, Stefan Both, Nanna Maria Sijtsema

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images.

Alessia De Biase, Wei Tang, Nikos Sourlos, Baoqiang Ma, Jiapan Guo, Nanna Maria Sijtsema, Peter M. A. van Ooijen

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021