Time-resolved MR angiography (tMRA) has been widely used for dynamic contrast enhanced MRI (DCE-MRI) due to its highly accelerated acquisition. In tMRA, the periphery of the k -space data are sparsely sampled so that neighbouring frames can be merged...
Intracranial blood vessel segmentation plays an essential role in the diagnosis and surgical planning of cerebrovascular diseases. Recently, deep convolutional neural networks have shown increasingly outstanding performance in image classification an...
We propose a novel deep learning based system for vessel segmentation. Existing methods using CNNs have mostly relied on local appearances learned on the regular image grid, without consideration of the graphical structure of vessel shape. Effective ...
Optical coherence tomography angiography (OCTA) is a relatively new imaging modality that generates microvasculature map. Meanwhile, deep learning has been recently attracting considerable attention in image-to-image translation, such as image denois...
PURPOSE: This study sought to determine the feasibility of using Simultaneous Non-contrast Angiography and intraPlaque Hemorrhage (SNAP) to detect the lipid-rich/necrotic core (LRNC), and develop a machine learning based algorithm to segment plaque c...
Despite advances in artificial intelligence (AI), its application in medical imaging has been burdened and limited by expert-generated labels. We used images from optical coherence tomography angiography (OCTA), a relatively new imaging modality that...
BACKGROUND: High urine flow rate (UFR) has been suggested as a target for effective prevention of contrast-induced acute kidney injury (CI-AKI). The RenalGuard therapy (saline infusion plus furosemide controlled by the RenalGuard system) facilitates ...
Automated feature extraction from medical images is an important task in imaging informatics. We describe a graph-based technique for automatically identifying vascular substructures within a vascular tree segmentation. We illustrate our technique us...
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
May 13, 2025
Deep learning (DL) is a subset of artificial intelligence based on deep neural networks. It has made remarkable breakthroughs in medical imaging, particularly for image classification and pattern recognition. In ophthalmology, there are rising intere...