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Articles 31 - 33 of 33
Full-Text Articles in Biomedical
Preliminary Study Based On The Ddscat Software To Explore Increasing The Contrast Of Breast Tumors For Microwave Imaging, Rachel Megee
Preliminary Study Based On The Ddscat Software To Explore Increasing The Contrast Of Breast Tumors For Microwave Imaging, Rachel Megee
Electrical Engineering Undergraduate Honors Theses
Microwave technology is being researched for its capabilities to detect breast tumors less painfully and at earlier stages. It is necessary to have a large contrast between cancerous and healthy tissue when the microwaves are reflected off the breast tissue. To model the increasing contrast between cancerous breast tissue and healthy breast tissue, the DDSCAT code is investigated for its capabilities and analyzed for its accuracy in scattering calculations. The DDSCAT is used to model homogenous and inhomogeneous targets. Simulations of the scattering field by the homogeneous and inhomogeneous targets are conducted and compared to Mie theory calculations for accuracy. …
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj
Electrical & Computer Engineering Faculty Research
The manual interpretation of MRI slices based on visual examination by radiologist/physician may lead to missing diagnosis when a large number of MRIs are analyzed. To avoid the human error, an automated intelligent classification system is proposed. This research paper proposes an intelligent classification technique to the problem of classifying four types of brain abnormalities viz. Metastases, Meningiomas, Gliomas, and Astrocytomas. The abnormalities are classified based on Two/Three/ Four class classification using statistical and textural features. In this work, classification techniques based on Least Squares Support Vector Machine (LS-SVM) using textural features computed from the MR images of patient are …
A Study Of Transconductance Degradation In Hemt Using A Self-Consistent Boltzmann-Poisson-Schrodinger Solver, Rahim Khoie
A Study Of Transconductance Degradation In Hemt Using A Self-Consistent Boltzmann-Poisson-Schrodinger Solver, Rahim Khoie
Electrical & Computer Engineering Faculty Research
A self-consistent Boltzmann-Poisson-Schrödinger Solver is used to study the transconductance degradation in high electron mobility transistor (HEMT), which has extensively been reported by both experimental [1]-[8] and computational [9]-[ 13] researchers. As the gate voltage of a HEMT device is increased, its transconductance increases until it reaches a peak value, beyond which, the transconductance is degraded rather sharply with further increase in applied gate bias. We previously reported a two-subband self-consistent Boltzmann-Poisson- Schrödinger Solver for HEMT. [14] We further incorporated an additional self-consistency by calculating field-dependent, energy-dependent intersubband and intrasubband scattering rates due to ionized impurities and polar optical phonons.[15] …