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Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter
Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter
Wayne State University Dissertations
Presented in this work is an investigation of the application of artificially intelligent algorithms, namely deep learning, to generate segmentations for the application in functional avoidance radiotherapy treatment planning. Specific applications of deep learning for functional avoidance include generating hippocampus segmentations from computed tomography (CT) images and generating synthetic pulmonary perfusion images from four-dimensional CT (4DCT).A single institution dataset of 390 patients treated with Gamma Knife stereotactic radiosurgery was created. From these patients, the hippocampus was manually segmented on the high-resolution MR image and used for the development of the data processing methodology and model testing. It was determined that …
Electrochemical Gelation Of Metal Chalcogenide Quantum Dots, Chathuranga Chinthana Hewa Rahinduwage
Electrochemical Gelation Of Metal Chalcogenide Quantum Dots, Chathuranga Chinthana Hewa Rahinduwage
Wayne State University Dissertations
Quantum dots (QDs) are attractive because of their unique size-dependent optical and electronic properties and high surface area. They are tested in research for diverse applications, including energy conversion, catalysis, and sensing. Assembling QDs into functional solid-state devices while preserving their attractive properties is a challenge. Methods currently under the research are not effective in directly fabricating QDs onto devices, making large area assemblies, maintaining the high surface area by forming 3D porous structures, and conducting electricity for applications such as sensing. QD gels are an example of QD assemblies that consist of a 3D porous interconnected QD network. They …
Optical Signal Processing With Discrete-Space Metamaterials, Mohammad Moein Moeini
Optical Signal Processing With Discrete-Space Metamaterials, Mohammad Moein Moeini
Wayne State University Dissertations
As digital circuits are approaching the limits of Moore’s law, a great deal of efforthas been directed to alternative computing approaches. Among them, the old concept of optical signal processing (OSP) has attracted attention, revisited in the light of metamaterials and nano-photonics. This approach has been successful in realizing basic mathematical operations, such as derivatives and integrals, but it is difficult to be applied to more complex ones. Inspired by digital filters, we propose a radically new OSP approach, able to realize arbitrary mathematical operations over a nano-photonic platform. We demonstrate this concept for the case of spatial differentiation, image …