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Stenosis Detection of X-Ray Coronary Angiographic Image Sequence

Published: 24 September 2021 Publication History

Abstract

Automatic lesion detection from coronary X-ray angiography images is important for the auxiliary diagnosis of coronary heart diseases. However, the current methods are inefficient, and the detection accuracy cannot meet the criteria of doctors. This paper proposes a two-step method including video phase partition and video stenosis detection to automatically identify coronary stenosis from the complete X-ray angiography (XRA) video. First, convolutional neural network and long short-term memory based spatial–temporal network are used to automatically extract a continuous video segment that is full of contrast agent. Second, a detection network for attention video object is used to accurately and efficiently discern coronary stenosis on the continuous video segment. In the experiment, 166 video data were used for training and testing. The accuracy of video phase partition network can reach 0.838, and the precision and F1 of video stenosis detection results are 0.8 and 0.76 respectively. This performance is the best among all comparison methods. Therefore, we have implemented a complete process for detecting stenoses from coronary XRA sequences.

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ICCAI '21: Proceedings of the 2021 7th International Conference on Computing and Artificial Intelligence
April 2021
498 pages
ISBN:9781450389501
DOI:10.1145/3467707
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 24 September 2021

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Author Tags

  1. X-ray angiography
  2. stenosis detection
  3. video object detection
  4. video phase partition

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  • Key Technology Research and Development Program of the National Ministry of Science award number(s)
  • National Science Foundation Program of China award number(s)

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ICCAI '21

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