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Magnetic resonance imaging (MRI) and computed tomography (CT) are the main diagnostic tools in clinics, but their high cost, large size, and lengthy detection times drive researchers to seek new methods for identifying brain injuries. Many researchers detect cerebral hemorrhage by analyzing electromagnetic variations in brain regions using electromagnetic induction. Initial feasibility assessments of this method should be validated through simulation experiments that include developing a brain model. The development of the model requires careful consideration of both simplicity and complexity. An overly simplistic model may compromise the accuracy of simulation results, while an excessively complex model can lead to increased computational time and higher hardware specifications. This paper presents a novel method for constructing a four-layer brain model that addresses these concerns effectively. The model comprises the scalp, skull, spinal fluid, and brain. 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