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 …
Brain vessel segmentation using deep learning—a review
This article provides a comprehensive review of deep learning-based blood vessel
segmentation of the brain. Cerebrovascular disease develops when blood arteries in the …
segmentation of the brain. Cerebrovascular disease develops when blood arteries in the …
Geometric deep learning using vascular surface meshes for modality-independent unruptured intracranial aneurysm detection
Early detection of unruptured intracranial aneurysms (UIAs) enables better rupture risk and
preventative treatment assessment. UIAs are usually diagnosed on Time-of-Flight Magnetic …
preventative treatment assessment. UIAs are usually diagnosed on Time-of-Flight Magnetic …
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 …
USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging
Performance metrics for medical image segmentation models are used to measure the
agreement between the reference annotation and the predicted segmentation. Usually …
agreement between the reference annotation and the predicted segmentation. Usually …
Calibration techniques for node classification using graph neural networks on medical image data
Miscalibration of deep neural networks (DNNs) can lead to unreliable predictions and hinder
their use in clinical decision-making. This miscalibration is often caused by overconfident …
their use in clinical decision-making. This miscalibration is often caused by overconfident …
Deep-learning-based extraction of circle of Willis topology with anatomical priors
Abstract The circle of Willis (CoW) is a circular arrangement of arteries in the human brain,
exhibiting significant anatomical variability. The CoW is extensively studied in relation to …
exhibiting significant anatomical variability. The CoW is extensively studied in relation to …
Contour attention network for cerebrovascular segmentation from TOF‐MRA volumetric images
Background Cerebrovascular segmentation is a crucial step in the computer‐assisted
diagnosis of cerebrovascular pathologies. However, accurate extraction of cerebral vessels …
diagnosis of cerebrovascular pathologies. However, accurate extraction of cerebral vessels …
Deep learning with vessel surface meshes for intracranial aneurysm detection
It is important that unruptured intracranial aneurysms (UIAs) are detected early for rupture
risk and treatment assessment. Radiologists usually visually diagnose UIAs on Time-of …
risk and treatment assessment. Radiologists usually visually diagnose UIAs on Time-of …
Anatomical Markers Associated With the Presence of Intracranial Aneurysms in Individuals Screened for Aneurysms
IN Vos, RJ van Tuijl, LA Mensing… - Stroke: Vascular and …, 2024 - Am Heart Assoc
BACKGROUND Hemodynamic stress is linked to the development of intracranial aneurysms
(IAs) and may be influenced by anatomic variation of intracranial arteries. We assessed …
(IAs) and may be influenced by anatomic variation of intracranial arteries. We assessed …