Arteriovenous Malformation

Arteriovenous malformations (AVMs) are abnormal tangles of blood vessels that can occur in various locations, including the brain. Current research focuses on improving the diagnosis and treatment of AVMs using advanced imaging techniques like digital subtraction angiography (DSA) and computational methods such as deep learning (including convolutional neural networks and 3DUNet architectures) and formal concept analysis to better delineate vessel structures and predict AVM behavior. These efforts aim to improve the accuracy and efficiency of AVM detection and characterization, ultimately leading to better patient care and treatment planning. The development of robust, automated diagnostic tools holds significant promise for improving the management of AVMs and related conditions.