14.3k citations
- Harvard UniversityUS62 papers
- Athinoula A. Martinos Center for Biomedical ImagingUS26 papers
- Massachusetts Institute of TechnologyUS13 papers
- Harvard University PressUS9 papers
- German Center for Neurodegenerative DiseasesDE7 papers
- University College LondonGB6 papers
- Brigham and Women's HospitalUS5 papers
- Zhejiang UniversityCN5 papers
- Boston Children's HospitalUS4 papers
- InsermFR4 papers
- Peking UniversityCN4 papers
- Politecnico di TorinoIT4 papers
15 papers · 1 filter
GACELLE: GPU-accelerated tools for model parameter estimation and image reconstruction
Kwok-Shing Chan, Hansol Lee, Yixin Ma +4
Quantitative MRI (qMRI) offers tissue-specific biomarkers that can be tracked over time or compared across populations; however, its adoption in clinical research is hindered by si…
Transformer-Based Local Feature Matching for Multimodal Image Registration
Remi Delaunay, Ruisi Zhang, Filipe C. Pedrosa +4
Ultrasound imaging is a cost-effective and radiation-free modality for visualizing anatomical structures in real-time, making it ideal for guiding surgical interventions. However,…
TabAttention: Learning Attention Conditionally on Tabular Data
Michal K. Grzeszczyk, Szymon Płotka, Beata Rebizant +6
Medical data analysis often combines both imaging and tabular data processing using machine learning algorithms. While previous studies have investigated the impact of attention me…
AngioMoCo: Learning-based Motion Correction in Cerebral Digital Subtraction Angiography
Ruisheng Su, Matthijs van der Sluijs, Sandra Cornelissen +6
Cerebral X-ray digital subtraction angiography (DSA) is the standard imaging technique for visualizing blood flow and guiding endovascular treatments. The quality of DSA is often n…
Posterior Estimation Using Deep Learning: A Simulation Study of Compartmental Modeling in Dynamic PET
Xiaofeng Liu, Thibault Marin, Tiss Amal +3
Background: In medical imaging, images are usually treated as deterministic, while their uncertainties are largely underexplored. Purpose: This work aims at using deep learning to…
3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images
Sungmin Hong, Razvan Marinescu, Adrian V. Dalca +4
Image synthesis via Generative Adversarial Networks (GANs) of three-dimensional (3D) medical images has great potential that can be extended to many medical applications, such as,…