20.10.6.2 Atrial Fibrillation

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Atrial Fibrillation.

Kara, S.[Sadik], Okandan, M.[Mustafa],
Atrial fibrillation classification with artificial neural networks,
PR(40), No. 11, November 2007, pp. 2967-2973.
WWW Link. 0707
Electrocardiography; Atrial fibrillation; Artificial neural network; Wavelet; Welch method; Power spectral density BibRef

Manzke, R., Meyer, C., Ecabert, O., Peters, J., Noordhoek, N.J., Thiagalingam, A., Reddy, V.Y., Chan, R.C., Weese, J.,
Automatic Segmentation of Rotational X-Ray Images for Anatomic Intra-Procedural Surface Generation in Atrial Fibrillation Ablation Procedures,
MedImg(29), No. 2, February 2010, pp. 260-272.
IEEE DOI 1002
BibRef

Brost, A.[Alexander], Wimmer, A.[Andreas], Liao, R.[Rui], Bourier, F., Koch, M., Strobel, N.[Norbert], Kurzidim, K., Hornegger, J.[Joachim],
Constrained Registration for Motion Compensation in Atrial Fibrillation Ablation Procedures,
MedImg(31), No. 4, April 2012, pp. 870-881.
IEEE DOI 1204
BibRef

Brost, A.[Alexander], Wimmer, A.[Andreas], Liao, R.[Rui], Hornegger, J.[Joachim], Strobel, N.[Norbert],
Catheter Tracking: Filter-Based vs. Learning-Based,
DAGM10(293-302).
Springer DOI 1009
BibRef

Brost, A.[Alexander], Liao, R.[Rui], Hornegger, J.[Joachim], Strobel, N.[Norbert],
Model-Based Registration for Motion Compensation during EP Ablation Procedures,
WBIR10(234-245).
Springer DOI 1007
BibRef

Krueger, M.W., Seemann, G., Rhode, K., Keller, D.U.J., Schilling, C., Arujuna, A., Gill, J., O'Neill, M.D., Razavi, R., Dossel, O.,
Personalization of Atrial Anatomy and Electrophysiology as a Basis for Clinical Modeling of Radio-Frequency Ablation of Atrial Fibrillation,
MedImg(32), No. 1, January 2013, pp. 73-84.
IEEE DOI 1301
BibRef

Zheng, Y.F.[Ye-Feng], Yang, D.[Dong], John, M., Comaniciu, D.,
Multi-Part Modeling and Segmentation of Left Atrium in C-Arm CT for Image-Guided Ablation of Atrial Fibrillation,
MedImg(33), No. 2, February 2014, pp. 318-331.
IEEE DOI 1403
blood vessels BibRef

Baumert, M., Sanders, P., Ganesan, A.,
Quantitative-Electrogram-Based Methods for Guiding Catheter Ablation in Atrial Fibrillation,
PIEEE(104), No. 2, February 2016, pp. 416-431.
IEEE DOI 1601
Atrial fibrillation BibRef

Pourbabaee, B., Roshtkhari, M.J., Khorasani, K.,
Deep Convolutional Neural Networks and Learning ECG Features for Screening Paroxysmal Atrial Fibrillation Patients,
SMCS(48), No. 12, December 2018, pp. 2095-2104.
IEEE DOI 1812
convolution, electrocardiography, feature extraction, feedforward neural nets, learning (artificial intelligence), paroxysmal atrial fibrillation (PAF) BibRef

Gadaleta, M., Rossi, M., Topol, E.J., Steinhubl, S.R., Quer, G.,
On the Effectiveness of Deep Representation Learning: The Atrial Fibrillation Case,
Computer(52), No. 11, November 2019, pp. 18-29.
IEEE DOI 1911
medical diagnostic computing, time series, unsupervised learning, deep representation learning, atrial fibrillation case, Discrete wavelet transforms BibRef

Faust, O.[Oliver], Kareem, M.[Murtadha], Shenfield, A.[Alex], Ali, A.[Ali], Acharya, U.R.[U Rajendra],
Validating the robustness of an internet of things based atrial fibrillation detection system,
PRL(133), 2020, pp. 55-61.
Elsevier DOI 2005
Intelligent internet of things, Deep learning, Atrial fibrillation, Heart rate, Blindfold validation BibRef

Prashar, N.[Navdeep], Sood, M.[Meenakshi], Jain, S.[Shruti],
Novel Cardiac Arrhythmia Processing using Machine Learning Techniques,
IJIG(20), No. 3, July 2020, pp. 2050023.
DOI Link 2008
BibRef


Potse, M.[Mark], Vinet, A.[Alain], Gharaviri, A.[Ali], Pezzuto, S.[Simone],
Fibrillation Patterns Creep and Jump in a Detailed Three-Dimensional Model of the Human Atria,
FIMH19(131-138).
Springer DOI 1906
BibRef

Roy, A.[Aditi], Varela, M.[Marta], Chubb, H.[Henry], MacLeod, R.S.[Robert S.], Hancox, J.[Jules], Schaeffter, T.[Tobias], O'Neill, M.[Mark], Aslanidi, O.[Oleg],
Virtual Catheter Ablation of Target Areas Identified from Image-Based Models of Atrial Fibrillation,
FIMH19(11-19).
Springer DOI 1906
BibRef

Li, X., Alikhani, I., Shi, J., Seppanen, T., Junttila, J., Majamaa-Voltti, K., Tulppo, M., Zhao, G.,
The OBF Database: A Large Face Video Database for Remote Physiological Signal Measurement and Atrial Fibrillation Detection,
FG18(242-249)
IEEE DOI 1806
Biomedical monitoring, Databases, Electrocardiography, Face, Heart rate variability, Radio frequency, atrial fibrillation, heart rate variability BibRef

Jia, S.[Shuman], Camaioni, C.[Claudia], Rohé, M.M.[Marc-Michel], Jaïs, P.[Pierre], Pennec, X.[Xavier], Cochet, H.[Hubert], Sermesant, M.[Maxime],
Prediction of Post-Ablation Outcome in Atrial Fibrillation Using Shape Parameterization and Partial Least Squares Regression,
FIMH17(311-321).
Springer DOI 1706
BibRef

Zaidi, A.M.A., Ahmed, M.J., Bakibillah, A.S.M.,
Feature extraction and characterization of cardiovascular arrhythmia and normal sinus rhythm from ECG signals using LabVIEW,
IVPR17(1-6)
IEEE DOI 1704
Atrial fibrillation BibRef

Connolly, A.[Adam], Bishop, M.J.[Martin J.],
The Role of Endocardial Trabeculations in Low-Energy Defibrillation,
FIMH15(412-420).
Springer DOI 1507
BibRef

Donoso, F.[Felipe], Lecannelier, E.[Eduardo], Pino, E.[Esteban], Rojas, A.[Alejandro],
Reliable Atrial Activity Extraction from ECG Atrial Fibrillation Signals,
CIARP11(621-629).
Springer DOI 1111
BibRef

Karim, R.[Rashed], Gao, G.[Gang], Harrison, J.[James], Arujuna, A.[Aruna], Lambert, H.[Hendrik], Leo, G.[Giovanni], Gill, J.[Jaswinder], Razavi, R.[Reza], Schaeffter, T.[Tobias], O'Neill, M.[Mark], Rhode, K.S.[Kawal S.],
Mapping Contact Force during Catheter Ablation for the Treatment of Atrial Fibrillation: New Insights into Ablation Therapy,
FIMH11(302-303).
Springer DOI 1105
BibRef

Das, S., Chakraborty, M.,
Extraction of Fibrillation Components from Ventricular Arrhythmic Electrocardiograms,
NCVPRIPG11(138-141).
IEEE DOI 1205
BibRef

Couceiro, R., Carvalho, P., Henriques, J., Antunes, M., Harris, M., Habetha, J.,
Detection of Atrial Fibrillation using model-based ECG analysis,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Govindan, A.[Anupama], Deng, G.[Guang], Kalman, J., Power, J.[John],
Independent Component Analysis Applied to Electrogram Classification During Atrial Fibrillation,
ICPR98(Vol II: 1662-1664).
IEEE DOI 9808
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Myocardial Infarction .


Last update:Sep 24, 2020 at 19:44:22