IRIS: interactive real-time feedback image segmentation with deep learning

Egger, J. (Speaker)

Activity: Talk or presentationTalk at conference or symposiumScience to science

Description

Volumetric examinations of the aorta are nowadays of crucial importance for the management of critical pathologies such as aortic dissection, aortic aneurism, and other pathologies, which affect the morphology of the artery. In this work, we introduce a hybrid approach by combining a deep learning method with a consolidated interaction technique. In particular, we trained a 2D and 3D U-net on a limited number of patches extracted from 25 labeled CTA scans. Afterwards, we use an interactive approach, which consists in defining a region of interest (ROI) by just placing a seed point. This seed point is later used as the center of a 2D or 3D patch to be fed to the 2D or 3D U-net, respectively. Due to the low content variation of these patches, this method allows to correctly segment the ROIs without the need for parameter tuning for each dataset and with a smaller training dataset, requiring the same minimal interaction as state-of-the-art interactive methods.
Period28 Feb 2020
Event titleSPIE MEDICAL IMAGING 2020
Event typeConference
LocationHouston, United States, Texas
Degree of RecognitionInternational