Advanced Computational Intelligence Techniques For Hypoglycemia Monitoring System

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Microwaves imaging recognition by using advanced computational intelligence on biomedical applications (breast cancer detection) RESEARCH AREA OF INTEREST : HEALTH TECHNOLOGIES
This project aims to develop improved microwave imaging algorithms using radar based time reversal signal processing coupled with tomographic reconstruction to solve for the inverse source and scattering problems that arise in microwave imaging for localization of suspicious tissue regions as well as to estimate the shapes and dielectric properties of potentially malignant lesions within highly dense breasts. Computational Breast Phantoms using …show more content…

The technique used for detection in microwave imaging is based on the contrast in the dielectric properties between healthy and malignant breast tissues. Breasts consist of a mixture of fatty, adipose, epithelial and connective tissues. Dense breast tissue results from a large percentage of epithelial and connective tissues, collectively referred to as fibro glandular tissues.
It is well established from radiographic images that malignant breast tumours have irregular spiculated shapes and usually hide inside healthy fibro glandular regions.
The challenge faced by any existing imaging is to distinguish the malignant breast tissues from healthy fibro glandular tissue regions. Another compelling potential application is the characterization of the relative density of tissues in a healthy breast using microwave imaging as the high breast density is strongly correlated with cancer risk. The breast density estimation via microwave imaging can help to identify high-risk subjects before cancer has manifested. In addition, microwave imaging can also be used in monitoring the response of a tumour to other treatment protocols. These require dielectric mapping of the breast in addition to localization of malignant tissue. 2. AIMS AND OBJECTIVES
This project will make a significant contribution to knowledge in the modelling and design of a non-invasive medical condition monitor using physiological responses. In particular, the project aims to:

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