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Microwave imaging has grown in recent years as a promising technique for breast cancer detection. Its physical principle exploits the different dielectric characteristics of normal and tumoral breast tissues. In 2007 a study evaluated the dielectric properties of normal (adipose, glandular and fibroconnective), malignant (invasive and non-invasive ductal and lobular carcinomas) and benign (fibroadenomas and cysts) breast tissue samples obtained from cancer surgeries and breast reduction. The analyses showed that the contrast in the microwave-frequency dielectric properties between malignant lesions and glandular/fibroconnective tissues in the breast is no more than 10%. It is therefore fundamental to add to the electromagnetic issues signal processing reconstruction techniques that could improve the capability to correctly reconstruct the dielectric profile of the examined tissue. In this work we present different signal processing algorithms applied on microwave imaging of a phantom of the breast, analyzing their performances in order to migrate to clinical test campaigns on patients.