Segment aorta and localize landmarks simultaneously on noncontrast CT using a multitask learning framework for patients without severe vascular disease

Segment aorta and localize landmarks simultaneously on noncontrast CT using a multitask learning framework for patients without severe vascular disease

Background: Non-contrast chest CT is widely used for lung cancer screening, and its images carry potential information of the thoracic aorta. The morphological assessment of the thoracic aorta may have potential value in the presymptomatic detection of thoracic aortic-related diseases and the risk p...

Full description

Bibliographic Details
Main Authors: Cheng, J.-Z (Author), Ji, Y. (Author), Li, X. (Author), Shi, F. (Author), Wang, X. (Author), Xue, Z. (Author), Yang, F. (Author), Yang, J. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2023
Subjects:
Aorta segmentation
Aorta segmentations
Blood vessels
Chest CT
Computerized tomography
Deep learning
Diagnosis
Landmark detection
Landmark localization
Learning frameworks
Learning systems
Localisation
Mean square error
Morphology
Multitask learning
Noncontrast CT
Risk assessment
Subnets
Thoracic aorta
Online Access:View Fulltext in Publisher
View in Scopus

Internet

View Fulltext in Publisher
View in Scopus

Similar Items