Posts Tagged ‘cancer’
At ICIAM 2011, speakers from varying backgrounds, including Professors Patrick Nelson, Kerry Landman, and Avner Friedman, and graduate student Irina Kareva, outlined the many aspects of mathematical modeling in disease progression and dynamics, emphasizing the connections between mathematics and medical science.
Watch a video that highlights the applications of math modeling in diabetes, cancer and wound healing:
You can also read about Avner Friedman’s other research—on math modeling for cancer treatments here.
The most popular method of breast cancer detection today is X-ray mammography, which takes images of a compressed breast by low-dose ionizing radiation. However, there are several disadvantages to using X-rays for breast cancer screening, chief among them being the invasivity of radiation and the high costs, which limit their wide use and can deter women from getting them. In addition, depending on the age of the patient and tissue density, X-ray mammograms often result in false positives and negatives.
Microwave tomography can provide a cheaper and less risky alternative to X-ray mammography. In a paper published today in the SIAM Journal on Applied Mathematics, the authors describe a mathematical model for imaging tumors in the breast using microwave tomography. Read the rest of this entry »