33 citations
- Siemens Healthineers (Germany)DE8 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE6 papers
- Siemens (United States)US6 papers
- Siemens (Germany)DE3 papers
- Chinese Academy of Medical Sciences & Peking Union Medical CollegeCN2 papers
- Chinese University of Hong KongHK2 papers
- East China Normal UniversityCN2 papers
- Imperial College LondonGB2 papers
- King's College LondonGB2 papers
- New York UniversityUS2 papers
- Renji HospitalCN2 papers
- Shanghai Jiao Tong UniversityCN2 papers
32 papers
A novel unsupervised machine learning strategy to handle multimodal cardiac PET/MRI data
Brunnhilde Ponsi, Thomas Carlier, Lara Marteau +5
Arrhythmogenic left ventricular cardiomyopathy is a genetic myocardial disease difficult to diagnose due to the lack of gold standard criteria. Simultaneous PET/MR imaging, combine…
Dynamic Modulated Arc Therapy (DMAT): A Time Aware, Modulation Steered Optimization Framework for Next Generation Radiotherapy Delivery
Taoran Li, Esa Kuusela, Emmi Ruokokoski +10
Background: Conventional VMAT optimization treats delivery time and deliverability as emergent properties of control-point-centric models that ignore finite acceleration and other…
A Position Statement on Endovascular Models and Effectiveness Metrics for Mechanical Thrombectomy Navigation, on behalf of the Stakeholder Taskforce for AI-assisted Robotic Thrombectomy (START)
Harry Robertshaw, Anna Barnes, Phil Blakelock +20
While we are making progress in overcoming infectious diseases and cancer; one of the major medical challenges of the mid-21st century will be the rising prevalence of stroke. Larg…
Cut to the Mix: Simple Data Augmentation Outperforms Elaborate Ones in Limited Organ Segmentation Datasets
Chang Liu, Fuxin Fan, Annette Schwarz +1
Multi-organ segmentation is a widely applied clinical routine and automated organ segmentation tools dramatically improve the pipeline of the radiologists. Recently, deep learning…
Stroke Lesion Segmentation in Clinical Workflows: A Modular, Lightweight, and Deployment-Ready Tool
Yann Kerverdo, Florent Leray, Youwan Mahé +2
Deep learning frameworks such as nnU-Net achieve state-of-the-art performance in brain lesion segmentation but remain difficult to deploy clinically due to heavy dependencies and m…
Dipolar order mapping based on spin-lock magnetic resonance imaging
Zijian Gao, Qianxue Shan, Ziqin Zhou +2
Purpose: Inhomogeneous magnetization transfer (ihMT) effect reflects dipolar order with a dipolar relaxation time (), specific to motion-restricted macromolecules. We aim t…