High content imaging is a rapidly evolving technique which makes quantitative analysis of multiple events in a population of cultured cells. The evolution with time is also studied. A new generation of fully automated systems acquires images entire cultured cell populations with multimodal quantitative information (high-throughput microscope) but using conventional methods like fluorescence microscopy. Multispectral data is combined thanks to advanced data analysis algorithms. Biological study processes are in a large majority based on fluorescence imaging. This implies labelling the cells and induces some bias on their behavior. In addition long term time-lapse imaging (over hours) are tough to implement because fluorophores are very weak against excitation light: They rapidly photobleach. To proceed unbiased long-term studies, label-free techniques are to be promoted. The industrial partner Phasics has developed a quantitative phase imaging camera that answers this need. This new label-free technique reaches high contrast and low-noise tissue and cell images. In addition, the images contain quantitative information on the cell components, which is used as supplementary parameters for multispectral studies. The PhaseQuantHD project aims at developing a high-content imaging system using quadriwave lateral shearing interferometry as a quantitative phase imaging modality. Automated analysis methods will be developed and optimized for this modality. Finally an open biological study question will be treated with the system. The proposed multidisciplinary consortium combines the Phasics company and three academic partners: mathematicians and biologists. Phasics will integrate the quantitative phase into high-throughput systems that are already used by the academic partners. Phasics will perform specific technological developments including an optimization of the processing and acquisition time of quantitative phase images. In parallel, innovative automated analysis tools will be developed by mathematicians using two methodological pathways. The first will be based on supervised classification directly using gradients produced by the camera in order to optimize the information obtained from the samples. The second will be based on the possibility offered by the quantitative phase images to automatically define the space occupied by each cell as well as its biomass, and then to longitudinally monitor each cell. This project will promote the development of innovative tools for biologists. These tools will directly be evaluated by the consortium. The most innovative image processing methods will be patented. This project will also promote quantitative phase microscopy for high content imaging and give Phasics access to this fast growing market.