The elemental imaging of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) provides spatial information on elements and therefore can further investigate the growth or evolution processes of an analyte. However, the accurate determination of spatial information is limited by the decoupling between the elemental distribution and mass spectrometry signals. This phenomenon, which is more distinct when high-diffusion ablation cells are used, arises from the overlap of ablation and the transport dispersion of aerosols. Reconstruction of the elemental distribution using mathematical algorithms is an effective approach to addressing this decoupling. This study establishes a comprehensive numerical inversion method that targets the independent events of aerosol diffusion and overlapping ablation in LA-ICP-MS. A new signal fitting model and deconvolution algorithm are employed to mitigate the effects of aerosol diffusion. Moreover, boundary identification and restoration algorithms are developed to resolve the challenges posed by blurring of the phase boundary when the laser beam scans over the two-phase interface. By employing the presented numerical method, the shape of fine materials can be measured with an accuracy of 10%, which is an ∼18-fold improvement compared to the raw data. The new algorithm is expected to enhance the accuracy of the spatial distribution in LA-ICP-MS elemental imaging, particularly for traditional high-diffusion ablation cells, which are still in use in microanalytical laboratories on a global scale. Additionally, the numerical inversion method presented here can be applied across various fields of science to improve the quality of element imaging.