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Early Brain Tumor Detection by Early Glioblastoma Modeling and Quantum Fixed-Point MR Imaging

Abstract

Magnetic Resonance Imaging has been introduced for several decades; however, it is still difficult to distinguish the turmeric cell from the surrounding healthy cell at early stage due to the similarity of the micro environments. People are usually too late when they recognize their disease. My research goal is to model the difference in tumor cells’ environment and explore a new way to discover the disease. To achieve that, one of the fMRI technique (Blood Oxygenation Level Dependent--BOLD) together with Monte Carlo simulation of tumor cell and healthy cell were generated, and the results were comparable with in-vivo mouse model. In the second part, a new approach of quantum fixed-point spin dynamic was found to be profound on enhancement of contrast between healthy and tumor cell in MRI. With the designed pulse sequence, the home-build active feedback-controlled electronic device can differentiate the almost indistinguishable resonance offset from tumor cell and accelerate the magnetization towards the unique stable fixed points. Lastly, the spin dynamic under the active feedback source and the spin evolution under natural damping was analyzed in order to improve the understanding of the fixed points and allow for better modification of pulse sequence.

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