A U-Net deep learning framework for high performance vessel segmentation in patients with cerebrovascular disease
Brain vessel status is a promising biomarker for better prevention and treatment in
cerebrovascular disease. However, classic rule-based vessel segmentation algorithms need …
cerebrovascular disease. However, classic rule-based vessel segmentation algorithms need …
Deep learning for 3D vascular segmentation in hierarchical phase contrast tomography: a case study on kidney
Automated blood vessel segmentation is critical for biomedical image analysis, as vessel
morphology changes are associated with numerous pathologies. Still, precise segmentation …
morphology changes are associated with numerous pathologies. Still, precise segmentation …
3d brain and heart volume generative models: A survey
Generative models such as generative adversarial networks and autoencoders have gained
a great deal of attention in the medical field due to their excellent data generation capability …
a great deal of attention in the medical field due to their excellent data generation capability …
Synthesizing anonymized and labeled TOF-MRA patches for brain vessel segmentation using generative adversarial networks
Anonymization and data sharing are crucial for privacy protection and acquisition of large
datasets for medical image analysis. This is a big challenge, especially for neuroimaging …
datasets for medical image analysis. This is a big challenge, especially for neuroimaging …
[HTML][HTML] Generating 3D TOF-MRA volumes and segmentation labels using generative adversarial networks
Deep learning requires large labeled datasets that are difficult to gather in medical imaging
due to data privacy issues and time-consuming manual labeling. Generative Adversarial …
due to data privacy issues and time-consuming manual labeling. Generative Adversarial …
[HTML][HTML] eICAB: A novel deep learning pipeline for Circle of Willis multiclass segmentation and analysis
F Dumais, MP Caceres, F Janelle, K Seifeldine… - Neuroimage, 2022 - Elsevier
Background The accurate segmentation, labeling and quantification of cerebral blood
vessels on MR imaging is important for basic and clinical research, yet results are not …
vessels on MR imaging is important for basic and clinical research, yet results are not …
Association of collateral blood vessels detected by arterial spin labeling magnetic resonance imaging with neurological outcome after ischemic stroke
A de Havenon, DR Haynor, DL Tirschwell… - JAMA …, 2017 - jamanetwork.com
Importance Robust collateral blood vessels have been associated with better neurologic
outcome following acute ischemic stroke (AIS). The most commonly used methods for …
outcome following acute ischemic stroke (AIS). The most commonly used methods for …
Quantitative perfusion mapping with induced transient hypoxia using BOLD MRI
Purpose Gadolinium‐based dynamic susceptibility contrast (DSC) is commonly used to
characterize blood flow in patients with stroke and brain tumors. Unfortunately, gadolinium …
characterize blood flow in patients with stroke and brain tumors. Unfortunately, gadolinium …
Toward sharing brain images: differentially private TOF-MRA images with segmentation labels using generative adversarial networks
Sharing labeled data is crucial to acquire large datasets for various Deep Learning
applications. In medical imaging, this is often not feasible due to privacy regulations …
applications. In medical imaging, this is often not feasible due to privacy regulations …
Deep Learning for 3D Vascular Segmentation in Phase Contrast Tomography
Automated blood vessel segmentation is critical for biomedical image analysis, as vessel
morphology changes are associated with numerous pathologies. Still, precise segmentation …
morphology changes are associated with numerous pathologies. Still, precise segmentation …