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9 March 2020 Automated analysis of tissue heterogeneity based on OCT images for improving personalized cancer therapy effectiveness (Conference Presentation)
Mark Scimone, Gopi Maguluri, Jesung Park, Nicusor V. Iftimia
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Proceedings Volume 11234, Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis; 112340I (2020) https://doi.org/10.1117/12.2549156
Event: SPIE BiOS, 2020, San Francisco, California, United States
Abstract
In the current era of personalized cancer therapy, various drugs need to be rapidly tested to determine their efficacy in killing cancer cells. In this way, the most effective drug can be administered to improve therapy effectiveness. However, since the biopsy specimens are heterogeneous, efficient testing requires the use only of the viable tumor part of the specimen. Therefore, rapid and automated evaluation of specimen heterogeneity is needed. In this paper presents an automated algorithm for tissue heterogeneity estimation based on OCT images. This algorithm use image texture features to differentiate between healthy and cancer tissue.
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Mark Scimone, Gopi Maguluri, Jesung Park, and Nicusor V. Iftimia "Automated analysis of tissue heterogeneity based on OCT images for improving personalized cancer therapy effectiveness (Conference Presentation)", Proc. SPIE 11234, Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis, 112340I (9 March 2020); https://doi.org/10.1117/12.2549156
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KEYWORDS
Tissues
Cancer
Optical coherence tomography
Biological research
Biopsy
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