Myocardial Ischemia Detection Algorithm (MIDA): automated echocardiography sequence analysis for diagnosis of heart muscle damage

Vijayalakshmi Ahanathapillai; John Soraghan

Myocardial Ischemia Detection Algorithm (MIDA): automated echocardiography sequence analysis for diagnosis of heart muscle damage

Vijayalakshmi Ahanathapillai, John Soraghan

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

4 Citations (Scopus)

Abstract

A Myocardial Ischemia Detection Algorithm (MIDA) is presented that analyses echocardiography sequences automatically in order to detect the presence of heart
muscle damage. MIDA involves an image enhancement, fuzzy multi resolution edge detection to obtain the heart wall boundaries, composite motion image creation using
the heart wall boundaries, followed by statistical pattern recognition and classification to identify the heart wall abnormality. The performance of MIDA is assessed using 62 real patient data with both normal and abnormal conditions. The results indicate that MIDA can be used as an effective tool for automatically diagnosing Myocardial Ischemia

Original language	English
Title of host publication	Computing in Cardiology 2010
Editors	Alan Murray
Publisher	IEEE
Pages	405-408
Number of pages	4
ISBN (Print)	9781424473182
Publication status	Published - Dec 2010
Event	International Conference on Computers in Cardiology - Belfast, United Kingdom Duration: 26 Sept 2010 → 29 Sept 2010

Conference

Conference	International Conference on Computers in Cardiology
Country/Territory	United Kingdom
City	Belfast
Period	26/09/10 → 29/09/10

Keywords

support vector machine classification
cavity resonators
feature extraction
heart
image edge detection
noise
principal component analysis

Cite this

@inproceedings{9ac657f771614f0685473d422a228698,

title = "Myocardial Ischemia Detection Algorithm (MIDA): automated echocardiography sequence analysis for diagnosis of heart muscle damage",

abstract = "A Myocardial Ischemia Detection Algorithm (MIDA) is presented that analyses echocardiography sequences automatically in order to detect the presence of heart muscle damage. MIDA involves an image enhancement, fuzzy multi resolution edge detection to obtain the heart wall boundaries, composite motion image creation using the heart wall boundaries, followed by statistical pattern recognition and classification to identify the heart wall abnormality. The performance of MIDA is assessed using 62 real patient data with both normal and abnormal conditions. The results indicate that MIDA can be used as an effective tool for automatically diagnosing Myocardial Ischemia",

keywords = "support vector machine classification , cavity resonators, feature extraction, heart, image edge detection, noise, principal component analysis",

author = "Vijayalakshmi Ahanathapillai and John Soraghan",

year = "2010",

month = dec,

language = "English",

isbn = "9781424473182",

pages = "405--408",

editor = "Murray, {Alan }",

booktitle = "Computing in Cardiology 2010",

publisher = "IEEE",

note = "International Conference on Computers in Cardiology ; Conference date: 26-09-2010 Through 29-09-2010",

}

TY - GEN

T1 - Myocardial Ischemia Detection Algorithm (MIDA)

T2 - International Conference on Computers in Cardiology

AU - Ahanathapillai, Vijayalakshmi

AU - Soraghan, John

PY - 2010/12

Y1 - 2010/12

N2 - A Myocardial Ischemia Detection Algorithm (MIDA) is presented that analyses echocardiography sequences automatically in order to detect the presence of heart muscle damage. MIDA involves an image enhancement, fuzzy multi resolution edge detection to obtain the heart wall boundaries, composite motion image creation using the heart wall boundaries, followed by statistical pattern recognition and classification to identify the heart wall abnormality. The performance of MIDA is assessed using 62 real patient data with both normal and abnormal conditions. The results indicate that MIDA can be used as an effective tool for automatically diagnosing Myocardial Ischemia

AB - A Myocardial Ischemia Detection Algorithm (MIDA) is presented that analyses echocardiography sequences automatically in order to detect the presence of heart muscle damage. MIDA involves an image enhancement, fuzzy multi resolution edge detection to obtain the heart wall boundaries, composite motion image creation using the heart wall boundaries, followed by statistical pattern recognition and classification to identify the heart wall abnormality. The performance of MIDA is assessed using 62 real patient data with both normal and abnormal conditions. The results indicate that MIDA can be used as an effective tool for automatically diagnosing Myocardial Ischemia

KW - support vector machine classification

KW - cavity resonators

KW - feature extraction

KW - heart

KW - image edge detection

KW - noise

KW - principal component analysis

UR - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5737995&isnumber=5737883

M3 - Conference contribution book

SN - 9781424473182

SP - 405

EP - 408

BT - Computing in Cardiology 2010

A2 - Murray, Alan

PB - IEEE

Y2 - 26 September 2010 through 29 September 2010

ER -

Myocardial Ischemia Detection Algorithm (MIDA): automated echocardiography sequence analysis for diagnosis of heart muscle damage

Abstract

Conference

Keywords

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