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Paper Abstract and Keywords
Presentation 2022-05-19 15:10
Arrhythmia catheter ablation point prediction from ECG and CT image based on machine learning
Kazuyuki Ohmura (GEHCJ), Kenichiro Yamagata, Kengo Kusano (NCVC), Nozomu Uetake (GEHCJ)
Abstract (in Japanese) (See Japanese page) 
(in English) Catheter ablation is the key therapy in treating arrhythmia. For this treatment planning, 3D electroanatomical map is used to find the origin but it needs the direct access to heart with electrode and requires the experience and long time to get detailed information. So if the origin can be predicted with CT image and ECG data before treatment, it improves the quality of treatment. This paper propose the model to predict catheter ablation origin from 12-lead ECG + position of electrodes and CT image.
Keyword (in Japanese) (See Japanese page) 
(in English) Arrhythmia / Catheter ablation / CT / ECG / Machine Learning / / /  
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Conference Information
Committee IEICE-SIP IEICE-BioX IEICE-IE IEICE-MI IST ME  
Conference Date 2022-05-19 - 2022-05-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Kumamoto University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IEICE-MI 
Conference Code 2022-05-SIP-BioX-IE-MI-IST-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Arrhythmia catheter ablation point prediction from ECG and CT image based on machine learning 
Sub Title (in English)  
Keyword(1) Arrhythmia  
Keyword(2) Catheter ablation  
Keyword(3) CT  
Keyword(4) ECG  
Keyword(5) Machine Learning  
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1st Author's Name Kazuyuki Ohmura  
1st Author's Affiliation GE Healthcare Japan Co. Ltd. (GEHCJ)
2nd Author's Name Kenichiro Yamagata  
2nd Author's Affiliation National Cerebral and Cardiovascular Center Department of Cardiovasular Medicine (NCVC)
3rd Author's Name Kengo Kusano  
3rd Author's Affiliation National Cerebral and Cardiovascular Center Department of Cardiovasular Medicine (NCVC)
4th Author's Name Nozomu Uetake  
4th Author's Affiliation GE Healthcare Japan Co. Ltd. (GEHCJ)
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Speaker Author-1 
Date Time 2022-05-19 15:10:00 
Presentation Time 20 minutes 
Registration for IEICE-MI 
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Volume (vol) vol.46 
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