Conventional systems for breast imaging include the use of x-ray technology, radar-based imaging, or magnetic resonance imaging (MRI). Digital breast tomosynthesis (DBT), which utilizes X-ray to create a three-dimensional image of the breast, provides a high-resolution image but the radiological contrast between the healthy fibrous tissue and cancerous tissue may be 1% or less. Near field radar imaging (NRI) may provide somewhat better radiological contrast but low-resolution image. However, the microwave NRI technology has two other disadvantages: first, the NRI algorithm assumes a homogenous background within the breast, which is unrealistic and fails to find cancerous tissue. Second, the NRI technology assumes fixed dielectric constants for each type of tissue (e.g. muscle, skin, fat, and fibrous tissue) in the breast, while each tissue has a scale of dielectric constants and the assumption of fixed constants result in erroneous modeling and imaging resolution. While MRI techniques have been proven to be successful in the detection of cancerous tissue, the acquisition time and cost of MRI signals would be great. Hence, a new method of imaging should be developed to overcome the limitations of existing technologies. 

Technology Overview

Researchers at Northeastern invented a new method for non-invasive detection of breast cancer, which is a hybrid of NRI and DBT. In this method, multiple DBT projections and NRI measurements are acquired simultaneously with the breast under clinical compression. The NRI system provides significant radiological contrast (at least 10%), which distinguishes fibroglandular tissue from cancerous tissue. The detection process of the NRI system is improved by the use of an accurate heterogenous background comprising granular dielectric constant values. This system leverage on dielectric constant between fat and other tissues to perform modeling to facilitate clutter reduction. The generated map is translated into a granular map of dielectric constant values for NRI processing which leads to improved cancerous and non-cancerous tissue differentiation. The imaging that has undergone such a process of clutter reduction provides an improved detection rate of anomalies. The complementary integrated DBT system scan the same tissue mass as the NRI and provide a high-resolution pixel-level distribution map of fat content. In this invention, mechanical scanning is used to collect data in a dense grid of points that enable the scattered data to be finely measured in spite of the reduced number of bulky wideband antennas in an available space. Also, the scattered data from the breast is collected in a two-dimensional array of receivers. This scheme for the data collection provides three-dimensional focusing capabilities to the system in addition to the Synthetic Aperture Radar (SAR) focusing derived from the mechanical scanning. 


  • Increased probability of cancer detection
  • High-resolution image 
  • High radiological contrast between cancerous and non-cancerous tissue
  • Providing accurate background information
  • Mechanical scanning of arrays in a reduced amount of time 
  • Three-dimensional array focusing and SAR focusing 


 Non-invasive detection of anomalies such as breast cancer 


  • License
  • Partnering
  • Research collaboration
Patent Information:
For Information, Contact:
Mark Saulich
Associate Director of Commercialization
Northeastern University
Jose Angel Martinez-Lorenzo
Carey Rappaport
Diagnostic Software
Imaging Technology