AI-Assisted Stanford Classification of Aortic Dissection in CT Imaging Using Volumetric 3D CNN with External Guided Attention

Cheng Fu Liou, Li Ting Huang, Paul Kuo, Chien Kuo Wang, Jiun In Guo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper reports an innovative approach to the classification of Stanford Type A and Type B aortic dissection using 3D CNN in conjunction with a novel Guided Attention (GA) mechanism. Recently, Computerized Tomography (CT) scan is increasingly applied for diagnoses of aortic dissection, and AI-assisted technology has been proven effective in increasing the productivity of radiologists. However, the general 3D CNN method even takes advantage of spatial continuity is not able to focus on the torn region of the aorta. In contrast, we propose an innovative approach termed the 'External Guided Attention' (EGA), which is capable of focusing on both global and local features and guiding the model to learn key representative of the lesion. The scheme has been modified such that inputs of grayscale images combining with EGA channels can be trained and fine-tuned like regular RGB image inputs, so the pre-trained model on RGB video sequences can be utilized. Finally, we demonstrate that our new approach significantly outperforms other attention methods on categorizing Stanford Type-A and Type-B aortic dissection where the accuracy of 0.991 and an AUC of 0.994 are achieved in our untrimmed test dataset.

Original languageEnglish
Title of host publicationBioCAS 2021 - IEEE Biomedical Circuits and Systems Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728172040
DOIs
Publication statusPublished - 2021
Event2021 IEEE Biomedical Circuits and Systems Conference, BioCAS 2021 - Virtual, Online, Germany
Duration: 2021 Oct 62021 Oct 9

Publication series

NameBioCAS 2021 - IEEE Biomedical Circuits and Systems Conference, Proceedings

Conference

Conference2021 IEEE Biomedical Circuits and Systems Conference, BioCAS 2021
Country/TerritoryGermany
CityVirtual, Online
Period21-10-0621-10-09

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Biomedical Engineering
  • Electrical and Electronic Engineering

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