Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.

Journal: Journal of vascular surgery

PMID: 33309556

Abstract

OBJECTIVE: Imaging software has become critical tools in the diagnosis and decision making for the treatment of abdominal aortic aneurysms (AAA). However, the interobserver reproducibility of the maximum cross-section diameter is poor. This study aimed to present and assess the quality of a new fully automated software (PRAEVAorta) that enables fast and robust detection of the aortic lumen and the infrarenal AAA characteristics including the presence of thrombus.

Authors

Caroline Caradu

Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France.
Benedetta Spampinato

Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France.
Ana Maria Vrancianu

Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France.
Xavier Bérard

Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France.
Eric Ducasse

Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France. Electronic address: eric.ducasse@chu-bordeaux.fr.

Keywords

Anatomic Landmarks Aortic Aneurysm, Abdominal Aortography Automation Computed Tomography Angiography Deep Learning Humans Multidetector Computed Tomography Observer Variation Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Retrospective Studies Software Design Workflow

External Resources

View on PubMed Access via DOI PubMed (33309556)

Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.

Abstract

Authors

Keywords

External Resources

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