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

Vijayalakshmi Ahanathapillai, John Soraghan

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

3 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
LanguageEnglish
Title of host publicationComputing in Cardiology 2010
EditorsAlan Murray
PublisherIEEE
Pages405-408
Number of pages4
ISBN (Print)9781424473182
Publication statusPublished - Dec 2010
EventInternational Conference on Computers in Cardiology - Belfast, United Kingdom
Duration: 26 Sep 201029 Sep 2010

Conference

ConferenceInternational Conference on Computers in Cardiology
CountryUnited Kingdom
CityBelfast
Period26/09/1029/09/10

Fingerprint

Echocardiography
Muscle
Pattern recognition
Image enhancement
Edge detection
Composite materials

Keywords

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

Cite this

Ahanathapillai, V., & Soraghan, J. (2010). Myocardial Ischemia Detection Algorithm (MIDA): automated echocardiography sequence analysis for diagnosis of heart muscle damage. In A. Murray (Ed.), Computing in Cardiology 2010 (pp. 405-408). IEEE.
Ahanathapillai, Vijayalakshmi ; Soraghan, John. / Myocardial Ischemia Detection Algorithm (MIDA) : automated echocardiography sequence analysis for diagnosis of heart muscle damage. Computing in Cardiology 2010. editor / Alan Murray. IEEE, 2010. pp. 405-408
@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 = "12",
language = "English",
isbn = "9781424473182",
pages = "405--408",
editor = "Murray, {Alan }",
booktitle = "Computing in Cardiology 2010",
publisher = "IEEE",

}

Ahanathapillai, V & Soraghan, J 2010, Myocardial Ischemia Detection Algorithm (MIDA): automated echocardiography sequence analysis for diagnosis of heart muscle damage. in A Murray (ed.), Computing in Cardiology 2010. IEEE, pp. 405-408, International Conference on Computers in Cardiology, Belfast, United Kingdom, 26/09/10.

Myocardial Ischemia Detection Algorithm (MIDA) : automated echocardiography sequence analysis for diagnosis of heart muscle damage. / Ahanathapillai, Vijayalakshmi; Soraghan, John.

Computing in Cardiology 2010. ed. / Alan Murray. IEEE, 2010. p. 405-408.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

TY - GEN

T1 - Myocardial Ischemia Detection Algorithm (MIDA)

T2 - automated echocardiography sequence analysis for diagnosis of heart muscle damage

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

ER -