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Carotid vessel wall segmentation through domain aligner, topological learning, and segment anything model for sparse annotation in mr images
Medical image analysis poses significant challenges due to limited availability of clinical
data, which is crucial for training accurate models. This limitation is further compounded by …
data, which is crucial for training accurate models. This limitation is further compounded by …
Vsr-net: Vessel-like structure rehabilitation network with graph clustering
The morphologies of vessel-like structures, such as blood vessels and nerve fibres, play
significant roles in disease diagnosis, eg, Parkinson's disease. Although deep network …
significant roles in disease diagnosis, eg, Parkinson's disease. Although deep network …
Learning Wall Segmentation in 3D Vessel Trees using Sparse Annotations
We propose a novel approach that uses sparse annotations from clinical studies to train a
3D segmentation of the carotid artery wall. We use a centerline annotation to sample …
3D segmentation of the carotid artery wall. We use a centerline annotation to sample …
Learning carotid vessel wall segmentation in black-blood MRI using sparsely sampled cross-sections from 3D data
Purpose Atherosclerosis of the carotid artery is a major risk factor for stroke. Quantitative
assessment of the carotid vessel wall can be based on cross-sections of three-dimensional …
assessment of the carotid vessel wall can be based on cross-sections of three-dimensional …
Uncertainty-based quality assurance of carotid artery wall segmentation in black-blood MRI
The application of deep learning models to large-scale data sets requires means for
automatic quality assurance. We have previously developed a fully automatic algorithm for …
automatic quality assurance. We have previously developed a fully automatic algorithm for …
[کتاب][B] Quantitative neuroimaging with handcrafted and deep radiomics in neurological diseases
E Lavrova - 2024 - search.proquest.com
The motivation behind this thesis is to explore the potential of" radiomics" in the field of
neurology, where early diagnosis and accurate treatment selection are crucial for improving …
neurology, where early diagnosis and accurate treatment selection are crucial for improving …
Carotid Artery Plaque Analysis in 3D Based on Distance Encoding in Mesh Representations
Purpose: Enabling a comprehensive and robust assessment of carotid artery plaques in 3D
through extraction and visualization of quantitative plaque parameters. These parameters …
through extraction and visualization of quantitative plaque parameters. These parameters …