Wavelet-SVM classification and automatic recognition of unstained viable cells in phase-contrast microscopy

Abstract

Irradiation of individual cultured mammalian cells with a pre-selected number of ions down to one ion per single cell is a useful experimental approach to investigating the low-dose ionising radiation exposure effects and thus contributing to a more realistic human cancer risk assessment. One of the crucial tasks of all the microbeam apparatuses is the visualisation, recognition and positioning of every individual cell of the cell culture to be irradiated. Before irradiations, mammalian cells (specifically, Chinese hamster V79 cells) are seeded and grown as a monolayer on a mylar surface used as the bottom of a specially designed holder. Manual recognition of unstained cells in a bright-field microscope is a time-consuming procedure; therefore, a parallel algorithm has been conceived and developed in order to speed up this irradiation protocol step. Many technical problems have been faced to overcome the complexity of the images to be analysed: cell discrimination in an inhomogeneous background, among many disturbing bodies mainly due to the mylar surface roughness and culture medium bodies; cell shapes, depending on how they attach to the surface, which phase of the cell cycle they are in and on cell density. Preliminary results of the recognition and classification based on a method of wavelet kernels for the support vector machine classifier will be presented.