Wei Zhao
Stony Brook University, NY·Biomedical Engineering
Mammograms are x-ray images of the breast. They catch many cancers, but dense breast tissue can hide tumors.
- Fields
Biomedical Engineering
Medicine & Clinical Research
Physics
- Topics
breast cancer
mammography
digital breast tomosynthesis
- Grants
- 1 known grant, through Feb 2028
What they work on
- Design, optimize and fabricate a prototype dual-layer flat-panel detector that records two mammograms at different x-ray energies in a single exposure, giving perfectly aligned images free of patient-motion artifacts.
- Develop spectral image-processing techniques for the detector using simulation, for dual-energy digital breast tomosynthesis with and without an iodine contrast agent that makes tumors stand out.
- Integrate the prototype into a clinical breast tomosynthesis system and test its dual-energy imaging performance in tissue-mimicking phantoms and patient imaging studies.
More about the research
Taking images at two x-ray energies adds contrast information that helps separate tissues. Doing this usually means two separate exposures, and if the patient moves between them, the images do not line up. This project aims to capture both energies at once with a single, low-cost detector.
Why it matters
Women undergoing breast cancer screening, diagnosis or treatment monitoring could benefit from x-ray images that carry extra contrast information without motion blur. Because the detector builds on mature, inexpensive detector technology, it could bring spectral breast imaging into clinics quickly and at low cost, which could improve detection of breast cancers.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Paul Schwoebel
University of New Mexico, NM·Biomedical Engineering
Design a two-dimensional stationary Multi-X-ray-source Array (MXA) for digital breast tomosynthesis, using modeling and experiments to choose a source layout that improves image quality within short scan times.
Christoph Lee
University of Wisconsin-Madison, WI·Medicine & Clinical Research
Validate a 2D mammography AI algorithm from the DREAM Digital Mammography Challenge on UCLA's Athena Breast Health Network registry, and refine it with radiologist supervision plus genetic mutation and tumor subtype data.
Mark Anastasio
Washington University in St Louis, MO·Biomedical Engineering
Develop multi-physics simulation tools that model light transport and sound detection to generate realistic 3D breast optoacoustic tomography (OAT) measurement data from numerical breast phantoms.
The school
Stony Brook University: 32 labs on PI Pages, $319M a year on research, 289 research doctorates a year.
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