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Image processing methods for computer-aided interpretation of cell lines for cancer studies

Sreejith L Das, Alamelu Nachiappan, Narendrakumar G, Karthikeyan J, CP Anitha Devi

This paper proposes computer based automated cancer cell line classification. The burden of manual labeling can be alleviated using the proposed method and will be a help for cancer research. The aim is to study the impact of metal complexes on cancer cell lines. In combination with thiosemicarbazone to form methyl, ethyl, phenyl groups were used for the study. Cultured Hep G2 cell lines are treated with Thiosemicarbazone metal complexes and the corresponding cell line structure variations were analysed. The synthesised cell line images are pre processed using a Hybrid Switching Filter. The filter denoises speckle noise which affects during image acquisition because of the faulty switching elements or poor lighting conditions. The filter makes use of a hybrid approach using linear and nonlinear concepts. These denoised images are segmented using boundary detectors. Canny’s algorithm is used for detecting the edges which makes use of abrupt pixel value variations. On analysing the factors such as time consumption, cost effectiveness and accuracy, this method can be used as a reliable decision maker in place of costly short tandem repeat (STR) analysis for laboratory studies.