Automatic frame classification and enhancement for CYSVIEW cystoscopy video

Shuang Chang; Sam S. Chang; Kristen Scarpato; Amy N. Luckenbaugh; Soheil Kolouri; Audrey K. Bowden

doi:10.1117/12.2649289

17 March 2023 Automatic frame classification and enhancement for CYSVIEW cystoscopy video

Shuang Chang, Sam S. Chang, Kristen Scarpato, Amy N. Luckenbaugh, Soheil Kolouri, Audrey K. Bowden

Proceedings Volume PC12353, Advanced Photonics in Urology 2023; PC1235306 (2023) https://doi.org/10.1117/12.2649289
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Blue light cystoscopy (BLC) and white light cystoscopy (WLC) are standard of care tools to image the bladder for suspicious areas of tumor development. Having clear, high-quality frames in cystoscopy videos are crucial to sensitive, efficient detection of bladder tumors. Vessel features carry rich information but are often lost or poorly visualized in frames containing illumination artifacts or impacted by impurities in the bladder. In our study, we introduced an automatic WLC and BLC classification method for cystoscopy video analysis and proposed an image enhancement pipeline that addresses the loss of features for cystoscopy videos containing WLC and BLC frames.

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Citation Download Citation

Shuang Chang, Sam S. Chang, Kristen Scarpato, Amy N. Luckenbaugh, Soheil Kolouri, and Audrey K. Bowden "Automatic frame classification and enhancement for CYSVIEW cystoscopy video", Proc. SPIE PC12353, Advanced Photonics in Urology 2023, PC1235306 (17 March 2023); https://doi.org/10.1117/12.2649289

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