Towards Personalized Management of Type B Aortic Dissection Using STENT: a STandard cta database with annotation of the ENtire aorta and True-false lumen

no code implementations • 3 Jan 2019 • Jianning Li, Long Cao, Yangyang Ge, Bowen Meng, Cheng Wang, Wei Guo

The database contains 274 CT angiography (CTA) scans from 274 unique TBAD patients and is split into a training set(254 cases including 210 preoperative and 44 postoperative scans ) and a test set(20 cases). Based on STENT, we develop a series of methods including automated TBAD segmentation and automated measurement of TBAD parameters that facilitate personalized and precise management of the disease.

Decision Making Management

Multi-Task Deep Convolutional Neural Network for the Segmentation of Type B Aortic Dissection

no code implementations • 26 Jun 2018 • Jianning Li, Long Cao, Yangyang Ge, W. Cheng, M. Bowen, G. Wei

Segmentation of the entire aorta and true-false lumen is crucial to inform plan and follow-up for endovascular repair of the rare yet life threatening type B aortic dissection.

Segmentation