Breast cancer represents one of the main reasons of death among women. As an alternative to the gold standard techniques for breast cancer diagnosis, microwave imaging has been proposed from research community and many microwave systems have been designed mainly to work at low microwave frequencies. Based both on the results of recent dielectric characterization campaigns on human breast ex-vivo tissues up to 50 GHz and on the promising feasibility studies of mm-wave imaging systems, in this article, we propose and test inverse scattering techniques as effective tool to process mm-wave data to image breast cancer. Differently from radar techniques so far adopted in conjunction with mm-wave imaging system, inverse scattering techniques turn out to be more versatile and robust with respect to the reduction of the amount of data and eventually also able to characterize the anomaly in terms of electromagnetic properties. In particular, in the above, two image reconstruction techniques, the Linear Sampling Method and the Born Approximation, are proposed and compared against both simulated and experimental data.