19 October 2017 Tissue multifractality and hidden Markov model based integrated framework for optimum precancer detection
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Abstract
We report the application of a hidden Markov model (HMM) on multifractal tissue optical properties derived via the Born approximation-based inverse light scattering method for effective discrimination of precancerous human cervical tissue sites from the normal ones. Two global fractal parameters, generalized Hurst exponent and the corresponding singularity spectrum width, computed by multifractal detrended fluctuation analysis (MFDFA), are used here as potential biomarkers. We develop a methodology that makes use of these multifractal parameters by integrating with different statistical classifiers like the HMM and support vector machine (SVM). It is shown that the MFDFA-HMM integrated model achieves significantly better discrimination between normal and different grades of cancer as compared to the MFDFA-SVM integrated model.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Sabyasachi Mukhopadhyay, Nandan K. Das, Indrajit Kurmi, Nirmalya Ghosh, Asima Pradhan, Prasanta K. Panigrahi, "Tissue multifractality and hidden Markov model based integrated framework for optimum precancer detection," Journal of Biomedical Optics 22(10), 105005 (19 October 2017). https://doi.org/10.1117/1.JBO.22.10.105005 . Submission: Received: 12 May 2017; Accepted: 29 September 2017
Received: 12 May 2017; Accepted: 29 September 2017; Published: 19 October 2017
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