An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography

Jianrui Ding; Min Xian; H. D. Cheng; Yingtao Zhang; Fei Xu

doi:10.1109/ICIP.2015.7351602

An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography

Jianrui Ding
, Min Xian
, H. D. Cheng
, Yingtao Zhang
, Fei Xu

School of Computer Science and Technology, Harbin Institute of Technology
Utah State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Transesophageal echocardiography (TEE) is widely used to detect left atrium (LA)/left atrial appendage (LAA) thrombi. In this paper, the local binary pattern variance (LBPV) features are extracted from region of interest (ROI). And the dynamic features are formed by using the information of its neighbor frames in the sequence. The sequence is viewed as a bag, and the ROIs in the sequence are considered as the instances. Multiple-instance learning (MIL) method is employed to solve the LAA thrombi detection. The experimental results show that the proposed method can achieve better performance than that by using other methods.

Original language	English
Title of host publication	2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
Publisher	IEEE Computer Society
Pages	4224-4227
Number of pages	4
ISBN (Electronic)	9781479983391
DOIs	https://doi.org/10.1109/ICIP.2015.7351602
State	Published - 9 Dec 2015
Externally published	Yes
Event	IEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada Duration: 27 Sep 2015 → 30 Sep 2015

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
Volume	2015-December
ISSN (Print)	1522-4880

Conference

Conference	IEEE International Conference on Image Processing, ICIP 2015
Country/Territory	Canada
City	Quebec City
Period	27/09/15 → 30/09/15

Keywords

Multiple-instance learning (MIL)
Transesophageal echocardiography (TEE)
left atrial appendage (LAA)
local binary pattern variance (LBPV)
thrombi detection

Access to Document

10.1109/ICIP.2015.7351602

Cite this

Ding, J., Xian, M., Cheng, H. D., Zhang, Y., & Xu, F. (2015). An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography. In 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings (pp. 4224-4227). Article 7351602 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2015-December). IEEE Computer Society. https://doi.org/10.1109/ICIP.2015.7351602

@inproceedings{a01074a492c84233bba7d340889fac46,

title = "An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography",

abstract = "Transesophageal echocardiography (TEE) is widely used to detect left atrium (LA)/left atrial appendage (LAA) thrombi. In this paper, the local binary pattern variance (LBPV) features are extracted from region of interest (ROI). And the dynamic features are formed by using the information of its neighbor frames in the sequence. The sequence is viewed as a bag, and the ROIs in the sequence are considered as the instances. Multiple-instance learning (MIL) method is employed to solve the LAA thrombi detection. The experimental results show that the proposed method can achieve better performance than that by using other methods.",

keywords = "Multiple-instance learning (MIL), Transesophageal echocardiography (TEE), left atrial appendage (LAA), local binary pattern variance (LBPV), thrombi detection",

author = "Jianrui Ding and Min Xian and Cheng, \{H. D.\} and Yingtao Zhang and Fei Xu",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Image Processing, ICIP 2015 ; Conference date: 27-09-2015 Through 30-09-2015",

year = "2015",

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day = "9",

doi = "10.1109/ICIP.2015.7351602",

language = "英语",

series = "Proceedings - International Conference on Image Processing, ICIP",

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Ding, J, Xian, M, Cheng, HD, Zhang, Y & Xu, F 2015, An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography. in 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings., 7351602, Proceedings - International Conference on Image Processing, ICIP, vol. 2015-December, IEEE Computer Society, pp. 4224-4227, IEEE International Conference on Image Processing, ICIP 2015, Quebec City, Canada, 27/09/15. https://doi.org/10.1109/ICIP.2015.7351602

An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography. / Ding, Jianrui; Xian, Min; Cheng, H. D. et al.
2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings. IEEE Computer Society, 2015. p. 4224-4227 7351602 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2015-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography

AU - Ding, Jianrui

AU - Xian, Min

AU - Cheng, H. D.

AU - Zhang, Yingtao

AU - Xu, Fei

PY - 2015/12/9

Y1 - 2015/12/9

N2 - Transesophageal echocardiography (TEE) is widely used to detect left atrium (LA)/left atrial appendage (LAA) thrombi. In this paper, the local binary pattern variance (LBPV) features are extracted from region of interest (ROI). And the dynamic features are formed by using the information of its neighbor frames in the sequence. The sequence is viewed as a bag, and the ROIs in the sequence are considered as the instances. Multiple-instance learning (MIL) method is employed to solve the LAA thrombi detection. The experimental results show that the proposed method can achieve better performance than that by using other methods.

AB - Transesophageal echocardiography (TEE) is widely used to detect left atrium (LA)/left atrial appendage (LAA) thrombi. In this paper, the local binary pattern variance (LBPV) features are extracted from region of interest (ROI). And the dynamic features are formed by using the information of its neighbor frames in the sequence. The sequence is viewed as a bag, and the ROIs in the sequence are considered as the instances. Multiple-instance learning (MIL) method is employed to solve the LAA thrombi detection. The experimental results show that the proposed method can achieve better performance than that by using other methods.

KW - Multiple-instance learning (MIL)

KW - Transesophageal echocardiography (TEE)

KW - left atrial appendage (LAA)

KW - local binary pattern variance (LBPV)

KW - thrombi detection

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Ding J, Xian M, Cheng HD, Zhang Y, Xu F. An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography. In 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings. IEEE Computer Society. 2015. p. 4224-4227. 7351602. (Proceedings - International Conference on Image Processing, ICIP). doi: 10.1109/ICIP.2015.7351602

An algorithm based on LBPV and MIL for left atrial thrombi detection using transesophageal echocardiography

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