20.10.6.3 Myocardial Infarction

Chapter Contents (Back)
Myocardial Infarction.

Detsky, J.S., Paul, G., Dick, A.J., Wright, G.A.,
Reproducible Classification of Infarct Heterogeneity Using Fuzzy Clustering on Multicontrast Delayed Enhancement Magnetic Resonance Images,
MedImg(28), No. 10, October 2009, pp. 1606-1614.
IEEE DOI 0910
BibRef

Tripathy, R.K., Dandapat, S.,
Detection of myocardial infarction from vectorcardiogram using relevance vector machine,
SIViP(11), No. 6, September 2017, pp. 1139-1146.
WWW Link. 1708
BibRef

Ukwatta, E., Arevalo, H., Li, K., Yuan, J., Qiu, W., Malamas, P., Wu, K.C., Trayanova, N.A., Vadakkumpadan, F.,
Myocardial Infarct Segmentation From Magnetic Resonance Images for Personalized Modeling of Cardiac Electrophysiology,
MedImg(35), No. 6, June 2016, pp. 1408-1419.
IEEE DOI 1606
Geometry BibRef

Duchateau, N., de Craene, M., Allain, P., Saloux, E., Sermesant, M.,
Infarct Localization From Myocardial Deformation: Prediction and Uncertainty Quantification by Regression From a Low-Dimensional Space,
MedImg(35), No. 10, October 2016, pp. 2340-2352.
IEEE DOI 1610
Computational modeling BibRef

Sharma, L.D.[Lakhan Dev], Sunkaria, R.K.[Ramesh Kumar],
Inferior myocardial infarction detection using stationary wavelet transform and machine learning approach,
SIViP(12), No. 2, February 2018, pp. 199-206.
WWW Link. 1802
BibRef

Baloglu, U.B.[Ulas Baran], Talo, M.[Muhammed], Yildirim, O.[Ozal], Tan, R.S.[Ru San], Acharya, U.R.[U Rajendra],
Classification of myocardial infarction with multi-lead ECG signals and deep CNN,
PRL(122), 2019, pp. 23-30.
Elsevier DOI 1904
Myocardial infarction, Deep learning, Multi-lead ECG, Biomedical signal BibRef

Lin, Z.C.[Zhuo-Chen], Gao, Y.X.[Yong-Xiang], Chen, Y.M.[Yi-Min], Ge, Q.[Qi], Mahara, G.[Gehendra], Zhang, J.X.[Jin-Xin],
Automated detection of myocardial infarction using robust features extracted from 12-lead ECG,
SIViP(14), No. 5, July 2020, pp. 857-865.
Springer DOI 2006
BibRef


Rumindo, G.K.[Gerardo Kenny], Duchateau, N.[Nicolas], Croisille, P.[Pierre], Ohayon, J.[Jacques], Clarysse, P.[Patrick],
Strain-Based Parameters for Infarct Localization: Evaluation via a Learning Algorithm on a Synthetic Database of Pathological Hearts,
FIMH17(106-114).
Springer DOI 1706
BibRef

Tang, Y.C.[Yee Chia], Bishop, M.J.[Martin J.],
Application of Diffuse Optical Reflectance to Measure Myocardial Wall Thickness and Presence of Infarct Scar: A Monte Carlo Simulation Study,
FIMH15(248-255).
Springer DOI 1507
BibRef

Denisko, D.[Danielle], Oduneye, S.[Samuel], Krahn, P.[Philippa], Ghate, S.[Sudip], Lashevsky, I.[Ilan], Wright, G.[Graham], Pop, M.[Mihaela],
Analysis of Activation-Recovery Intervals from Intra-cardiac Electrograms in a Pre-clinical Chronic Model of Myocardial Infarction,
FIMH17(280-288).
Springer DOI 1706
BibRef

Viallon, M., Spaltenstein, J.[Joel], de Bourguignon, C., Vandroux, C., Ammor, A., Romero, W., Bernard, O., Croisille, P., Clarysse, P.,
Automated Quantification of Myocardial Infarction Using a Hidden Markov Random Field Model and the EM Algorithm,
FIMH15(256-264).
Springer DOI 1507
BibRef

Eftestol, T., Maloy, F., Engan, K., Kotu, L.P., Woie, L., Orn, S.,
A texture-based probability mapping for localisation of clinically important cardiac segments in the myocardium in cardiac magnetic resonance images from myocardial infarction patients,
ICIP14(2227-2231)
IEEE DOI 1502
Entropy BibRef

Fritz, T., Jarrousse, O., Keller, D.U.J., Seemann, G., Dössel, O.,
In Silico Analysis of the Impact of Transmural Myocardial Infarction on Cardiac Mechanical Dynamics for the 17 AHA Segments,
FIMH11(241-249).
Springer DOI 1105
BibRef

Suinesiaputra, A.[Avan], Frangi, A.F.[Alejandro F.], Kaandorp, T.A.M.[Theodorus A. M.], Lamb, H.J.[Hildo J.], Bax, J.J.[Jeroen J.], Reiber, J.H.C.[Johan H. C.], Lelieveldt, B.P.F.[Boudewijn P. F.],
Slice-Based Combination of Rest and Dobutamine: Stress Cardiac MRI Using a Statistical Motion Model to Identify Myocardial Infarction: Validation against Contrast-Enhanced MRI,
FIMH11(267-274).
Springer DOI 1105
BibRef

Esteves, T.[Tiago], Valente, M.[Mariana], Nascimento, D.S.[Diana S.], Pinto-do-Ó, P.[Perpétua], Quelhas, P.[Pedro],
Automatic and Semi-automatic Analysis of the Extension of Myocardial Infarction in an Experimental Murine Model,
IbPRIA11(151-158).
Springer DOI 1106
BibRef

Metwally, M.K.[Mohamed K.], El-Gayar, N.[Neamat], Osman, N.F.[Nael F.],
Improved Technique to Detect the Infarction in Delayed Enhancement Image Using K-Mean Method,
ICIAR10(II: 108-119).
Springer DOI 1006
BibRef

Kerckhoffs, R.C.P.[Roy C. P.], McCulloch, A.D.[Andrew D.], Omens, J.H.[Jeffrey H.], Mulligan, L.J.[Lawrence J.],
Effect of Pacing Site and Infarct Location on Regional Mechanics and Global Hemodynamics in a Model Based Study of Heart Failure,
FIMH07(350-360).
Springer DOI 0706
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Medical Applications -- Coronary Arteries, Carotid Arteries .


Last update:Sep 14, 2020 at 15:32:18