抽象的な

Cancer Detection by Cell Segmentation Using Clustering and Watershed Algorithms

C.Ramya, V.Nirmala

Biopsy is one of the medical tests for skin cancer detection. A recent biopsy procedure requires invasive tissue removal from a living body. It is time consuming and complicated task. So non-invasive in-vivo virtual biopsy is preferable one, which is processed by automatic cell segmentation approach. The key component of the developed algorithms are Watershed transform that use the concept of morphological image processing and incorporate some principles of convergence index filter are used to segment cells in invivo virtual biopsy of human skin. This paper improves the success of automated cell segmentation for skin cancer diagnosis. This paper also presents different approaches involved in automated cell segmentation and identification of skin cancer at an earlier stage.