TIIS (한국인터넷정보학회)
Current Result Document : 1 / 1
| 한글제목(Korean Title) |
Artificial Intelligence-based Echocardiogram Video Classification by Aggregating Dynamic Information |
| 영문제목(English Title) |
Artificial Intelligence-based Echocardiogram Video Classification by Aggregating Dynamic Information |
| 저자(Author) |
Zi Ye
Yogan J. Kumar
Goh O. Sing
Fengyan Song
Xianda Ni
Jin Wang
|
| 원문수록처(Citation) |
VOL 15 NO. 02 PP. 0500 ~ 0521 (2021. 02) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Echocardiography, an ultrasound scan of the heart, is regarded as the primary physiological test for heart disease diagnoses. How an echocardiogram is interpreted also relies intensively on the determination of the view. Some of such views are identified as standard views because of the presentation and ease of the evaluations of the major cardiac structures of them. However, finding valid cardiac views has traditionally been time-consuming, and a laborious process because medical imaging is interpreted manually by the specialist. Therefore, this study aims to speed up the diagnosis process and reduce diagnostic error by providing an automated identification of standard cardiac views based on deep learning technology. More importantly, based on a brand-new echocardiogram dataset of the Asian race, our research considers and assesses some new neural network architectures driven by action recognition in video. Finally, the research concludes and verifies that these methods aggregating dynamic information will receive a stronger classification effect.
|
| 키워드(Keyword) |
Classification
Deep Learning
Echocardiogram View
LSTM
Two-Stream Network
|
| 파일첨부 |
PDF 다운로드
|
