This study introduces a hyperspectral imaging platform, PRM-SRS (Penalized Reference Matching Stimulated Raman Scattering), which integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering microscopy. The platform is designed to visualize and identify high-density lipoprotein particles, high cholesterol to phosphatidylethanolamine ratios, and subcellular distributions of sphingosine and cardiolipin in various biological samples. The PRM-SRS method enhances chemical specificity, subcellular resolution, and data processing speed compared to traditional imaging methods. It addresses the limitations of existing techniques, such as disruption of the native environment, limited spatial or spectral resolution, and inability to distinguish different lipid subtypes. The study demonstrates the effectiveness of PRM-SRS in mapping lipid distributions and metabolic dynamics in human kidney, mouse hippocampus, and human brain tissues, providing insights into lipid metabolism and potential applications in disease diagnosis and prognosis. The method's advantages include multiplexed lipid subtype visualization, positive similarity scores, and fast similarity score calculation, making it a robust tool for analyzing complex biological samples.This study introduces a hyperspectral imaging platform, PRM-SRS (Penalized Reference Matching Stimulated Raman Scattering), which integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering microscopy. The platform is designed to visualize and identify high-density lipoprotein particles, high cholesterol to phosphatidylethanolamine ratios, and subcellular distributions of sphingosine and cardiolipin in various biological samples. The PRM-SRS method enhances chemical specificity, subcellular resolution, and data processing speed compared to traditional imaging methods. It addresses the limitations of existing techniques, such as disruption of the native environment, limited spatial or spectral resolution, and inability to distinguish different lipid subtypes. The study demonstrates the effectiveness of PRM-SRS in mapping lipid distributions and metabolic dynamics in human kidney, mouse hippocampus, and human brain tissues, providing insights into lipid metabolism and potential applications in disease diagnosis and prognosis. The method's advantages include multiplexed lipid subtype visualization, positive similarity scores, and fast similarity score calculation, making it a robust tool for analyzing complex biological samples.