Smart Edge Computing

7Statistical Learning Approach for the Detection of Abnormalities in Cancer Cells for Finding Indication of Metastasis

Operational research into cancer has been going on for many years, but it has been very difficult to find out the rate of propagation of this disease and how it spreads abnormally in the different organs of the human body. When the malignant features of this disease spread at an exponential rate in the human body, then the shape and size of cancer cells increase abnormally and the cell concentration decreases gradually due to the presence of rotten holes. Statistical learning (SL) is one of the advanced techniques under operations research to analyze the post-image processing techniques over the cancerous image to understand the status of image assessment parameters, by which we can create an invariant shape descriptor methodology. This shape descriptor tool can easily determine the texture of the cells and other morphological features. Using this SL technique, the analysis of various image assessment parameters can be performed easily, and it is easy to determine whether there is a metastasis stage or not. In this chapter, we introduce the invariant shape descriptor tool with geodesic transformation, as well as z-transformation of carcinoma images. We have also shown the edge computation approaches over these images. The descriptor tool methodology is first applied to different letters of the alphabet, and then to different cancer cells of different organs ...