Diagnosing Heterogeneous Dynamics for CT Scan Images of Human Brain in Wavelet and MFDFA Domain
CT scan images of human brain of a particular patient in different cross sections are taken, on which wavelet transform and multi-fractal analysis are applied. The vertical and horizontal unfolding of images are done before analyzing these images. Discrete wavelet transform (DWT) through Daubechies basis are done for identifying fluctuations over polynomial trends for clear characterization of CT scan images of human brain in different cross-sections. A systematic investigation of de-noised images are carried out through wavelet normalized energy and wavelet semi-log plots, which clearly points out the mismatch between results of vertical and horizontal unfolding. The mismatch of results confirms the heterogeneity in spatial domain. Using the multi-fractal de-trended fluctuation analysis (MFDFA), the mismatch between the values of Hurst exponent and width of singularity spectrum by vertical and horizontal unfolding confirms the same.
KeywordsHuman Brain Discrete Wavelet Transform Hurst Exponent Biomedical Image Singularity Spectrum
The authors thank Bankura Sammilani Medical College and Hospital, Bankura, West Bengal for providing the CT images of human brain in different cross-section.
- 1.Alfano RR, Das BB, Cleary J, Prudente R, Celmer E (1991) Light sheds light on cancer distinguishing malignant tumors from benign tissues and tumors. Bull NY Acad Med 67(2):143–150Google Scholar
- 2.Ramanujam N (2000) Fluorescence spectroscopy of neoplastic and non-neoplastic tissues. Neoplasia 2(12):89Google Scholar
- 4.Schantz SP, Kolli V, Savage HE, Yu G, Shah JP, Harris DE, Katz A, Alfano RR, Huvos AG (1998) Invivo native cellular fluorescence and histological characteristics of head and neck cancer. Clin Cancer Res 4(5):1177–1182Google Scholar
- 8.Modi JK, Nanavati SP, Phadke AS, Panigrahi PK (2004) Wavelet transforms: application to data analysis-II. Resonance 8–13Google Scholar
- 9.Mukhopadhyay S, Das N, Pradhan A, Ghosh N, Panigrahi PK (2014) Pre-cancer detection by wavelet transform and multi-fractality in various grades of DIC stromal images. In: SPIE BIOS, USAGoogle Scholar
- 10.Mukhopadhyay S, Panigrahi PK (2013) Wind speed data analysis for various seasons during a decade by wavelet and S transform. Int J Comput Sci Technol 3(4) Google Scholar
- 11.Mukhopadhyay S, Das NK, Kumar R, Dash D, Mitra A, Panigrahi PK (2014) Study of the dynamics of wind data fluctuations: a wavelet and MFDFA based novel method. In: Elsevier Science and Technology Proceeding, IEMCONGRESS, IndiaGoogle Scholar
- 12.Mukhopadhyay S, Das NK, Pradhan A, Ghosh N, Panigrahi PK (2014) Wavelet and multi-fractal based analysis on DIC images in epithelium region to detect and diagnose the cancer progress among different grades of tissues. In: Proceedings of SPIE photonics EuropeGoogle Scholar