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Tumour classification with optimized sliding window size for OCT imaging

Publication ,  Conference
Čiževskis, O; Cugmas, B; Viškere, D; Melderis, M; Liepniece-Karele, I; Yao, J; Tamošiūnas, M
Published in: Progress in Biomedical Optics and Imaging - Proceedings of SPIE
January 1, 2022

Skin and subcutaneous tumors are widespread in dogs and cats. Current tumor diagnostics (e.g., biopsy, fine-needle cytology) is invasive and labor-consuming. In this work, we studied ex vivo the most common canine and feline tumor OCT images using sliding window analysis and linear SVC classification, and we compared different sliding window sizes to determine the most optimal window sizes when differentiating between skin, mast cell tumours and soft tissue sarcomas. Sensitivities and specificities of all tissue classes saw an increase with increasing window size at small window size values and plateaued at around 60-80 µm, indicating the most significant tissue structures for differentiation via SWA likely lay here. Our work is the first veterinary OCT study on multiple canine and feline skin tumors to optimize the sliding window size for image pattern analysis.

Duke Scholars

Published In

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

DOI

ISSN

1605-7422

ISBN

9781510647671

Publication Date

January 1, 2022

Volume

11948
 

Citation

APA
Chicago
ICMJE
MLA
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Čiževskis, O., Cugmas, B., Viškere, D., Melderis, M., Liepniece-Karele, I., Yao, J., & Tamošiūnas, M. (2022). Tumour classification with optimized sliding window size for OCT imaging. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 11948). https://doi.org/10.1117/12.2607185
Čiževskis, O., B. Cugmas, D. Viškere, M. Melderis, I. Liepniece-Karele, J. Yao, and M. Tamošiūnas. “Tumour classification with optimized sliding window size for OCT imaging.” In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 11948, 2022. https://doi.org/10.1117/12.2607185.
Čiževskis O, Cugmas B, Viškere D, Melderis M, Liepniece-Karele I, Yao J, et al. Tumour classification with optimized sliding window size for OCT imaging. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2022.
Čiževskis, O., et al. “Tumour classification with optimized sliding window size for OCT imaging.” Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 11948, 2022. Scopus, doi:10.1117/12.2607185.
Čiževskis O, Cugmas B, Viškere D, Melderis M, Liepniece-Karele I, Yao J, Tamošiūnas M. Tumour classification with optimized sliding window size for OCT imaging. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2022.

Published In

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

DOI

ISSN

1605-7422

ISBN

9781510647671

Publication Date

January 1, 2022

Volume

11948