24 March 2017 Optical diagnosis of cervical cancer by higher order spectra and boosting
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In this contribution, we report the application of higher order statistical moments using decision tree and ensemble based learning methodology for the development of diagnostic algorithms for optical diagnosis of cancer. The classification results were compared to those obtained with an independent feature extractors like linear discriminant analysis (LDA). The performance and efficacy of these methodology using higher order statistics as a classifier using boosting has higher specificity and sensitivity while being much faster as compared to other time-frequency domain based methods.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sawon Pratiher, Sawon Pratiher, Sabyasachi Mukhopadhyay, Sabyasachi Mukhopadhyay, Ritwik Barman, Ritwik Barman, Souvik Pratiher, Souvik Pratiher, Asima Pradhan, Asima Pradhan, Nirmalya Ghosh, Nirmalya Ghosh, Prasanta K. Panigrahi, Prasanta K. Panigrahi, } "Optical diagnosis of cervical cancer by higher order spectra and boosting", Proc. SPIE 10063, Dynamics and Fluctuations in Biomedical Photonics XIV, 100630W (24 March 2017); doi: 10.1117/12.2251237; https://doi.org/10.1117/12.2251237

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