References
- Bockeria O.L., Kislitsina O.N., Temirbulatova A.Sh. Magnitoelectrocardiographic potentialities in diagnosis of ischemic heart disease and rhythm disturbances. Annaly Aritmologii. 2009;2:45-63 (in Russ.).
- Volkova N.I., Dzherieva I.S., Zibarev A.L. Elektrokardiografiia (Electrocardiography). Moscow, 2022 (in Russ.). doi: 10.33029/9704-6443-4-CAR-2022-1-136
- Thaler M.S. The Only EKG Book You'll Ever Need. Wolters Kluwer, 2019. 361 p.
- Frank E. General Theory of Heart-Vector Projection. Circ. Res. 1954;2:258–270. doi: 10.1161/01.RES.2.3.258
- Dogrusoz Y.S., Rasoolzadeh N., Ondrusova B., Hlivák P. Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data. Frontiers in Physiology. 2023;14. doi: 10.3389/fphys.2023.1197778
- Holt J.H., Barnard A.C, Lynn M.S. A study of the human heart as a multiple dipole electrical source. II. Diagnosis and quantitation of left ventricular hypertrophy. Circulation. 1969;40(5):697–710. doi: 10.1161/01.CIR.40.5.697
- Esther P.-A. Automatic Detection of Extra-Cardiac Findings in Cardiovascular Magnetic Resonance. Lecture Notes in Computer Science. In: Medical Image Understanding and Analysis: 25th Annual Conference, MIUA 2021, Oxford, United Kingdom, July 12–14, 2021, Proceedings. Ed. Papiez B.W., Yaqub M., Jiao J., Namburete A.I.L., Noble J.A. Springer, 2021. P. 98–107. (Lecture Notes in Computer Science, V. 12722). doi: 10.1007/978-3-030-80432-9_8
- Takahata M., Shiono, Y., Taniguchi, M., Asae Y., Taruya A., Wada T., Ota S., Ozaki Y., Kashiwagi M., Kuroi A. et al. Qualitative and quantitative evaluation of microvascular obstruction with delayed enhancement cardiac computed tomography in patients with ST-segment elevation myocardial infarction. Int. J. Cardiovasc. Imaging. 2025. doi: 10.1007/s10554-025-03580-x
- Klarenberg H., Froeling M., Leiner T., Lamb H.J., Boekholdt S.M., Jorstad H.T., Strijkers G.J., Bakermans A.J. Exercise MRI stress testing of the human heart at 3 Tesla: measurement precision of biventricular function and aortic blood flow during steady-state bicycling exercise. Magnetic Resonance Materials in Physics, Biology and Medicine. 2025. doi: 10.1007/s10334-025-01304-9 2025
- Bernard O., Lalande A., Zotti C., Cervenansky F., Yang X., Heng P.-A., Cetin I., Lekadir K., Camara O., Ballester M.A.G. et al. Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? IEEE Trans Med Imaging. 2018;37:2514–2525. doi: 10.1109/TMI.2018.2837502
- Gorecka M., Craven T.P., Jex N., Chew P.G., Dobson L.E., Brown L.A.E., Higgins D.M., Thirunavukarasu S., Sharrack N., Javed W. et al. Mitral regurgitation assessment by cardiovascular magnetic resonance imaging during continuous in-scanner exercise: a feasibility study. Int. J. Cardiovasc. Imaging. 2024;40:1543–1553. doi: 10.1007/s10554-024-03141-8
- Koch H. Recent advances in magnetocardiography. Journal of Electrocardiology. 2004;37:117–122. doi: 10.1016/j.jelectrocard.2004.08.035
- Bauer S., Weber dos Santos R., Schmal T.R., Nagel E., Baer M., Koch H: QRS width and QT time alteration due to geometry change in modelled human cardiac magnetograms. IEEE Computers in Cardiology. 2005,;32:639–642. doi: 10.1109/CIC.2005.1588182
- Polikarpov M.A., Ustinin M.N., Rykunov S.D., Yurenya A.Y., Naurzakov S.P., Grebenkin A.P., Panchenko V.Y. 3D imaging of magnetic particles using the 7-channel magnetoencephalography device without pre-magnetization or displacement of the sample. J. Magn. Magn. Mater. 2017;427:39–143. doi: 10.1016/j.jmmm.2016.10.055
- Polikarpov M.A., Ustinin M.N., Rykunov S.D., Yurenya A.Y., Naurzakov S.P., Grebenkin A.P., Panchenko V.Y. Study of anisotropy of magnetic noise, generated by magnetic particles in geomagnetic field. J. Magn. Magn. Mater. 2019;475:620–626. doi: 10.1016/j.jmmm.2018.12.011
- Maslennikov Y.V. Magnetocardiographic diagnostic complexes based on the MAG_SKAN SQUIDs. J. Commun. Technol. Electron. 2011;56:991–999. doi: 10.1134/S1064226911050093
- Maslennikov Y.V., Primin M.A., Slobodchikov V.Yu., Khanin V.V., Nedayvoda I.V., Krymov V.A., Okunev A.V., Moiseenko E.A., Beljaev A.V., Rybkin V.S., Tolcheev A.V., Gapelyuk A.V. The DC-SQUID-based magnetocardiographic systems for clinical use. Phys. Procedia. 2012;36:88–93. doi: 10.1016/j.phpro.2012.06.218
- Giovangrandi L., Inan O., Wiard R., Etemadi M., Kovacs G. Ballistocardiography – a method worth revisiting. Conf. Proc. IEEE Eng. Med Biol. Soc. 2011:4279–4282. doi: 10.1109/IEMBS.2011.6091062
- Ustinin M.N., Boyko A.I., Rykunov S.D. Functional Tomography of Complex Systems Using Spectral Analysis of Multichannel Measurement Data. Pattern Recognit. Image Anal. 2023;33:1344–1374. doi: 10.1134/S1054661823040491
- Muller N.L. Computed tomography and magnetic resonance imaging: past, present and future. Eur. Respir. J. 2002;35:3–12. doi: 10.1183/09031936.02.00248202
- Mousseaux E., Tasu J.P., Jolivet O., Simonneau G., Bittoun J., Gaux J.-C.. Pulmonary arterial resistance: noninvasive measurement with indexes of pulmonary flow estimated at velocity-encoded MR imaging - preliminary experience. Radiology. 1999;212:896–902. doi: 10.1148/radiology.212.3.r99au21896
- McAdams H.P., Palmer S.M., Donnelly L.F., Charles H.C., Tapson V.F., MacFall J.R. Hyperpolarized 3He-enhanced MR imaging of lung transplant recipients: preliminary results. AJR. 1999;173(4):955–959. doi: 10.2214/ajr.173.4.10511156
- Qanadli S.D., Orvoen-Frija E., Lacombe P., Di Paola R., Bittoun J., Frija G. Estimation of gas and tissue lung volumes by MRI: functional approach of lung imaging. J. Comput. Assist. Tomogr. 1999;23:743–748. doi: 10.1097/00004728-199909000-00020
- Cluzel P., Similowski T., Chartrand-Lefebvre C., Zelter M., Derenne J.-P., Grenier P.A.. Diaphragm and chest wall: assessment of the inspiratory pump with MR imaging - preliminary observations. Radiology. 2000;215:574–583. doi: 10.1148/radiology.215.2.r00ma28574
- Goldman L.W. Principles of CT and CT Technology. J. Nucl. Med. Technol. 2007;35:115–128. doi: 10.2967/jnmt.107.042978
- Neal M.L., Kerckhoffs R. Current progress in patient-specific modeling. Brief. Bioinform. 2010;11:111–126. doi: 10.1093/bib/bbp049
- Niederer S.A., Plank G., Chinchapatnam P., Ginks M., Lamata P., Rhode K.S., Rinaldi C.A., Razavi R., Smith N.P. Length-dependent tension in the failing heart and the efficacy of cardiac resynchronization therapy. Cardiovascular Research. 2011;89:336–343. doi: 10.1093/cvr/cvq318
- Trayanova N.A. Whole-Heart Modeling: Applications to Cardiac Electrophysiology and Electromechanics. Circ. Res. 2011;108:113–128. doi: 10.1161/CIRCRESAHA.110.223610
- Aguado-Sierra J., Krishnamurthy A., Villongco C. Patient-Specific Modeling of Dyssynchronous Heart Failure: A Case Study. Prog. Biophys. Mol. Biol. 2011;107:147–155. doi: 10.1016/j.pbiomolbio.2011.06.014
- Llinás R.R., Ustinin M.N. Precise Frequency-Pattern Analysis to Decompose Complex Systems into Functionally Invariant Entities: U.S. Patent. US20140107979 A1. 2014.
- Rykunov, S.D., Boyko, A.I., Ustinin, M.N. Reconstruction of the Electrical Structure of the Human Body Using Spectral Functional Tomography. Pattern Recognit. Image Anal. 2023;33:1315–1343. doi: 10.1134/S1054661823040387
- Ustinin M.N., Maslennikov Yu.V., Rykunov S.D., Krymov V.A. Reconstruction of the Human Heart Functional Structure Based On a Few-Channel Magnetocardiogram. Ìàthematical Biology and Bioinformatics. 2018;13(2):392–401. doi: 10.17537/2018.13.392
- Llinás R.R., Ustinin M.N., Rykunov S., Walton K.D., Rabello G.M., Garcia J., Boyko A., Sychev V. Noninvasive muscle activity imaging using magnetography. Proceedings of the National Academy of Sciences of the United States of America. 2020;117(9):4942-4947. doi: 10.1073/pnas.1913135117
- Wagner P., Strodthoff N., Bousseljot R.-D., Kreiseler D., Lunze F.I., Samek W., Schaeffter T. PTB-XL, a large publicly available electrocardiography dataset. Sci. Data. 2020;7(1). Article No. 154. doi: 10.1038/s41597-020-0495-6
- Strodthoff N., Wagner P., Schaeffter T., Samek W. Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL. IEEE Journal of Biomedical and Health Informatics. 2020;25:1519–1528. doi: 10.1109/JBHI.2020.3022989
- Aras K., Good W., Tate J., Burton B., Brooks D., Coll-Font J., Doessel O., Schulze W., Potyagaylo D., Wang L., van Dam P., MacLeod R. S. Experimental Data and Geometric Analysis Repository (EDGAR). Journal of Electrocardiology. 2015;48(6):975–981. doi: 10.1016/j.jelectrocard.2015.08.008
- Willems L., Rubel P., Zywietz C. Standard interchange for computerized electrocardiography. Stud. Health Technol. Inform. 1993;6:185–194. doi: 10.3233/978-1-60750-850-2-185
- Moody G, Mark R. MIT-BIH Arrhythmia Database Version: 1.0.0. 2005. https://physionet.org/content/mitdb/1.0.0/ (accessed 03.12.2025).
- Goldberger A.L., Amaral L.A.N., Glass L., Hausdorff J.M., Ivanov P.C., Mark R.G., Mietus J.E., Moody G.B., Peng C.-K., Eugene H. Physiobank, PhysioToolkit, and PhysioNet components of a new research resource for complex physiologic signals. Circulation. 2000;101: e215–e220. doi: 10.1161/01.CIR.101.23.e215
- Couderc J.-P. A unique digital electrocardiographic repository for the development of quantitative electrocardiography and cardiac safety: the Telemetric and Holter ECG Warehouse (THEW). J. Electrocardiol. 2010;43:595–600. doi: 10.1016/j.jelectrocard.2010.07.015
- Oh T.I., Kim H.J., Jeong W.C., H.Wi. Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter. BioMedical Engineering. 2014;13(87). doi: 10.1186/1475-925X-13-87
- Koch H., Bousseljot RD., Kosch, O., Jahnke C., Paetsch I., Fleck E., Schnackenburg B. A reference dataset for verifying numerical electrophysiological heart models. BioMedical Engineering. 2011;10(11). doi: 10.1186/1475-925X-10-11
- Chen C., Liu Y., Schniter P., Tong M., Zareba K., Simonetti O., Potter L., Ahmad R. OCMR (v1.0)--Open-Access Multi-Coil k-Space Dataset for Cardiovascular Magnetic Resonance Imaging. arXiv: 2008.03410 [eess.IV]. doi: Cite to nonCR doi: 10.48550/arXiv.2008.03410
- Gharleghi R., Adikari D., Ellenberger K., Webster M., Ellis C., Sowmya A., Ooi S., Beier S. Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries. Sci. Data. 2023;10. Article No. 128. doi: 10.1038/s41597-023-02016-2
|
|
|