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6 March 2023 Optical coherence tomography texture analysis and classification of breast biopsies
Margherita Firenze, Yunhe Liu, Diana Mojahed, Nisha Gandhi, Hanina Hibshoosh, Richard Ha, Christine P. Hendon
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Proceedings Volume PC12368, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XXI; PC123680H (2023) https://doi.org/10.1117/12.2652988
Event: SPIE BiOS, 2023, San Francisco, California, United States
Abstract
Within this work we explore texture analysis of optical coherence tomography images and machine learning for automated detect classification of breast biopsies. Under an approved IRB protocol, breast biopsy specimens from 100 patients were imaged with a high resolution OCT system providing 3.7 micron axial resolution. The texture features extracted were first order statistics (histogram distribution) and second order statistics (such as GLCM). Binary classification was carried out for two cases: 1) risk 0 (no risk of cancer) versus everything else and 2) risk 3 (cancer) versus everything else.
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Margherita Firenze, Yunhe Liu, Diana Mojahed, Nisha Gandhi, Hanina Hibshoosh, Richard Ha, and Christine P. Hendon "Optical coherence tomography texture analysis and classification of breast biopsies", Proc. SPIE PC12368, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XXI, PC123680H (6 March 2023); https://doi.org/10.1117/12.2652988
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KEYWORDS
Biopsy
Breast
Biological research
Coherence (optics)
Binary data
Image classification
Feature extraction
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