57 citations · 111 across the 9 of their papers we have counts for
10 papers
Deep Learning for Cancer Prognosis Prediction Using Portrait Photos by StyleGAN Embedding
Amr Hagag, Ahmed Gomaa, Dominik Kornek +5
Survival prediction for cancer patients is critical for optimal treatment selection and patient management. Current patient survival prediction methods typically extract survival i…
The Segment Anything foundation model achieves favorable brain tumor autosegmentation accuracy on MRI to support radiotherapy treatment planning
Florian Putz, Johanna Grigo, Thomas Weissmann +13
Background: Tumor segmentation in MRI is crucial in radiotherapy (RT) treatment planning for brain tumor patients. Segment anything (SA), a novel promptable foundation model for au…
Benchmarking ChatGPT-4 on ACR Radiation Oncology In-Training (TXIT) Exam and Red Journal Gray Zone Cases: Potentials and Challenges for AI-Assisted Medical Education and Decision Making in Radiation Oncology
Yixing Huang, Ahmed Gomaa, Sabine Semrau +12
The potential of large language models in medicine for education and decision making purposes has been demonstrated as they achieve decent scores on medical exams such as the Unite…
Risk Classification of Brain Metastases via Radiomics, Delta-Radiomics and Machine Learning
Philipp Sommer, Yixing Huang, Christoph Bert +5
Stereotactic radiotherapy (SRT) is one of the most important treatment for patients with brain metastases (BM). Conventionally, following SRT patients are monitored by serial imagi…
Deep learning for automatic head and neck lymph node level delineation provides expert-level accuracy
Thomas Weissmann, Yixing Huang, Stefan Fischer +16
Background: Deep learning (DL)-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still…
Continual Learning for Peer-to-Peer Federated Learning: A Study on Automated Brain Metastasis Identification
Yixing Huang, Christoph Bert, Stefan Fischer +5
Due to data privacy constraints, data sharing among multiple centers is restricted. Continual learning, as one approach to peer-to-peer federated learning, can promote multicenter…
Learning Perspective Deformation in X-Ray Transmission Imaging
Yixing Huang, Andreas Maier, Fuxin Fan +5
In cone-beam X-ray transmission imaging, perspective deformation causes difficulty in direct, accurate geometric assessments of anatomical structures. In this work, the perspective…
Deep learning for brain metastasis detection and segmentation in longitudinal MRI data
Yixing Huang, Christoph Bert, Philipp Sommer +10
Brain metastases occur frequently in patients with metastatic cancer. Early and accurate detection of brain metastases is very essential for treatment planning and prognosis in rad…
An Investigation of Feature-based Nonrigid Image Registration using Gaussian Process
Siming Bayer, Ute Spiske, Jie Luo +8
For a wide range of clinical applications, such as adaptive treatment planning or intraoperative image update, feature-based deformable registration (FDR) approaches are widely emp…
Decoupling Respiratory and Angular Variation in Rotational X-ray Scans Using a Prior Bilinear Model
Tobias Geimer, Paul Keall, Katharina Breininger +4
Data-driven respiratory signal extraction from rotational X-ray scans is a challenge as angular effects overlap with respiration-induced change in the scene. In this paper, we use…