In this work, we report a wavelet based multi-fractal study of images of
dysplastic and neoplastic HE- stained human cervical tissues captured in the
transmission mode when illuminated by a laser light (He-Ne 632.8nm laser). It
is well known that the morphological changes occurring during the progression
of diseases like cancer manifest in their optical properties which can be
probed for differentiating the various stages of cancer. Here, we use the
multi-resolution properties of the wavelet transform to analyze the optical
changes. For this, we have used a novel laser imagery technique which provides
us with a composite image of the absorption by the different cellular
organelles. As the disease progresses, due to the growth of new cells, the
ratio of the organelle to cellular volume changes manifesting in the laser
imagery of such tissues. In order to develop a metric that can quantify the
changes in such systems, we make use of the wavelet-based fluctuation analysis.
The changing self- similarity during disease progression can be well
characterized by the Hurst exponent and the scaling exponent. Due to the use of
the Daubechies' family of wavelet kernels, we can extract polynomial trends of
different orders, which help us characterize the underlying processes
effectively. In this study, we observe that the Hurst exponent decreases as the
cancer progresses. This measure could be relatively used to differentiate
between different stages of cancer which could lead to the development of a
novel non-invasive method for cancer detection and characterization.Comment: 9 pages, 11 figures, 1 table, to appear in the Proceedings of SPIE
Photonics West, BiOS 201