PI-uMSS: Prior information-based unsupervised magnetic source separation in quantitative susceptibility mapping

data, infers intermediate parameters, and reconstructs the spatial distributions of paramagnetic and diamagnetic sources via biophysical modeling. Experimental results show that the method achieves high structural similarity (SSIM = 0.9945 for paramagnetic and 0.9942 for diamagnetic components) and a low normalized mean square error (0.11) relative to the original QSM, demonstrating robust and consistent source decomposition performance. Code is available at https://github.com/TyrionJ/PI-uMSS.