Aortic dissection is a life-threatening condition caused by a tear in the aortic wall, leading to blood flow in both the true lumen and the false lumen between the wall layers. Medical imaging plays a crucial role in diagnosis, treatment planning, and monitoring. CT Angiography (CTA) and MRI provide detailed images for accurate diagnosis and classification, while 3D reconstruction aids in pre-surgical planning and device selection. Regular imaging follow-ups with CTA or MRI monitor progression and treatment efficacy. Additionally, artificial intelligence (AI) enhances predictive analytics and automated measurements, improving diagnostic accuracy and personalized treatment planning. Integrating these imaging techniques significantly improves patient outcomes in aortic dissection management.
CIS-UNET: Multi-class Aortic Segmentation
Novel context-aware shifted window self-attention block for efficient segmentation of subtle, complex, and heterogeneous objects.
Automated Deep Learning Aortic Zone Segmentation Model
A deep learning model was created to assess volumetric growth in patients with acute uncomplicated type B aortic dissection, marking a significant advancement in medical imaging analysis.
