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The bidomain model (BD) The bidomain model (see, e.g., ref. 3) is based on the assumption that the extracellular space, the membrane and the intracellular space all exist everywhere in the tissue.

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In this work, we propose a novel bidomain modeling paradigm for pansharpening problem (dubbed as BiMPan), which takes into both local spectral specificity and global spatial detail. More specifically, we first customize the specialized source-discriminative adaptive convolution (SDAConv) for every spectral band instead of sharing the identical.

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The electrical bidomain model is the preferred model for simulating electrical stimulation of the heart, such as during cardiac pacing or defibrillation, when the crucial consideration is how a voltage develops across the membrane (Efimov et al., 2000; Trayanova and Plank, 2009). The mechanical bidomain model may be similarly useful when.

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Training and testing codes are in the current folder. The code for training is in main.py, while the code for testing test.py. For training, you need to set the file_path in the main function, adopt t your train set, validate set, and test set as well. Our code train the .h5 file, you may change it through changing the code in main function.

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The electrocardiogram (ECG) is an essential clinical tool for the non-invasive assessment of cardiac function. Computational simulations of ECGs using bidomain models are considered the biophysically most detailed approach, but computational costs are significant. Alternatively, pseudo-bidomain formulations can be used, combining a monodomain.

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The bidomain model, initially introduced in [8, 24, 19], is the standard tissue-level model of cardiac electrophysiology widely used in simulations (see for instance [4, 15, 17, 6, 23]). Well-posedness is studied in [7, 3, 25, 5, 11, 12]. It is possible

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2.1 The Bidomain Model. The focus of this convergence analysis is the macroscopic cardiac Bidomain model [20, 44], which describes the propagation of the electric signal in the cardiac tissue by means of a degenerate Footnote 1 system of parabolic partial differential equations (PDEs).In this model, the cardiac tissue (known as myocardium) is described as the composition of two ohmic.

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Overview. The bidomain model was originally derived by Tung [ 19] and can be written as a system of nonlinear ordinary and partial differential equations (ODEs and PDEs). Several alternative formulations exist, but the one most frequently used for computations is written in terms of the variables u e , v, and s, which represent respectively the.

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The bidomain model (BD) 1 has become a valuable tool for understanding cardiac electrophysiology. It has been used, for instance, to study the effects of electrical defibrillation 2,3,4, to.

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Abstract. Cardiac muscle is made up of coupled myocytes, embedded in an interstitial space comprised of blood vessels, connective tissue, fibroblasts fluid, and other cell types and adjoining some extracellular fluid. The bidomain model was originally developed to describe the current flow in both these three spaces using continuous partial.

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The bidomain model is a mathematical model to define the electrical activity of the heart.It consists in a continuum (volume-average) approach in which the cardiac microstructure is defined in terms of muscle fibers grouped in sheets, creating a complex three-dimensional structure with anisotropical properties. Then, to define the electrical activity, two interpenetrating domains are.

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4.2.2 Monodomain model. The bidomain model of cardiac tissue (Equation (6)) can be simplified by assuming that the anisotropy of the intracellular and extracellular spaces is the same, i.e. that the conductivity in the extracellular space is proportional to the intracellular conductivity: (8) where is a scalar, representing the ratio between.