Label-free digital histopathology for human breast cancer grading at the subcellular level

Yi Xiao; Shaolong Xue; Shiyuan Wei; Renjie Zhou

doi:10.1117/12.2610602

2 March 2022 Label-free digital histopathology for human breast cancer grading at the subcellular level

Yi Xiao, Shaolong Xue, Shiyuan Wei, Renjie Zhou

Proceedings Volume PC11970, Quantitative Phase Imaging VIII; PC119700X (2022) https://doi.org/10.1117/12.2610602
Event: SPIE BiOS, 2022, San Francisco, California, United States

Conference Poster

Abstract

The current gold standard for tissue histopathology is based on the examination of stained tissue slices by pathologists. To save time and minimize human efforts, computerized methods in nuclei segmentation and classification have been advanced and popularized for histopathology applications. Digital histopathology has been increasingly applied to cancer diagnosis and prognosis. We proposed a label-free digital histopathology method based on refractive index maps measured from a large field of view optical diffraction tomography system. We measured breast cancer tissue slices and digitally processed the data for cancer grading.

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Citation Download Citation

Yi Xiao, Shaolong Xue, Shiyuan Wei, and Renjie Zhou "Label-free digital histopathology for human breast cancer grading at the subcellular level", Proc. SPIE PC11970, Quantitative Phase Imaging VIII, PC119700X (2 March 2022); https://doi.org/10.1117/12.2610602

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