作者: Yang Dong , Shaoxiong Liu , Yuanxing Shen , Honghui He , Hui Ma
DOI: 10.1364/BOE.397441
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摘要: Recently, we developed a label-free method to probe the microstructural information and optical properties of unstained thin tissue slices based on microscopic Mueller matrix imaging technique. In this paper, take images human breast ductal carcinoma samples at different pathological stages, then calculate analyze their retardance-related matrix-derived parameters. To reveal features more quantitatively precisely, propose new first-order statistical image transform 2D parameters into several feature vectors. We evaluate each vector by corresponding classification characteristic value extracted from healthy duct samples. The experimental results indicate that these vectors derived may become powerful tools characterize stages. It has potential facilitate automating staging process tissue, resulting in improvement diagnostic efficiency.