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Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter Jan 2022

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 …


Catgame: A Tool For Problem Solving In Complex Dynamic Systems Using Game Theoretic Knowledge Distribution In Cultural Algorithms, And Its Application (Catneuro) To The Deep Learning Of Game Controller, Faisal Waris Jan 2020

Catgame: A Tool For Problem Solving In Complex Dynamic Systems Using Game Theoretic Knowledge Distribution In Cultural Algorithms, And Its Application (Catneuro) To The Deep Learning Of Game Controller, Faisal Waris

Wayne State University Dissertations

Cultural Algorithms (CA) are knowledge-intensive, population-based stochastic optimization methods that are modeled after human cultures and are suited to solving problems in complex environments. The CA Belief Space stores knowledge harvested from prior generations and re-distributes it to future generations via a knowledge distribution (KD) mechanism. Each of the population individuals is then guided through the search space via the associated knowledge. Previously, CA implementations have used only competitive KD mechanisms that have performed well for problems embedded in static environments. Relatively recently, CA research has evolved to encompass dynamic problem environments. Given increasing environmental complexity, a natural question arises …


The Use Of Cultural Algorithms To Learn The Impact Of Climate On Local Fishing Behavior In Cerro Azul, Peru, Khalid Kattan Jan 2019

The Use Of Cultural Algorithms To Learn The Impact Of Climate On Local Fishing Behavior In Cerro Azul, Peru, Khalid Kattan

Wayne State University Dissertations

Recently it has been found that the earth’s oceans are warming at a pace that is 40% faster than predicted by a United Nations panel a few years ago. As a result, 2019 has become the warmest year on record for the earth’s oceans. That is because the oceans have acted as a buffer by absorbing 93% of the heat produced by the greenhouse gases [40].

The impact of the oceanic warming has already been felt in terms of the periodic warming of the Pacific Ocean as an effect of the ENSO process. The ENSO process is a cycle of …


Capso: A Multi-Objective Cultural Algorithm System To Predict Locations Of Ancient Sites, Samuel Dustin Stanley Jan 2019

Capso: A Multi-Objective Cultural Algorithm System To Predict Locations Of Ancient Sites, Samuel Dustin Stanley

Wayne State University Dissertations

ABSTRACT

CAPSO: A MULTI-OBJECTIVE CULTURAL ALGORITHM SYSTEM TO PREDICT LOCATIONS OF ANCIENT SITES

by

SAMUEL DUSTIN STANLEY

August 2019

Advisor: Dr. Robert Reynolds

Major: Computer Science

Degree: Doctor of Philosophy

The recent archaeological discovery by Dr. John O’Shea at University of Michigan of prehistoric caribou remains and Paleo-Indian structures underneath the Great Lakes has opened up an opportunity for Computer Scientists to develop dynamic systems modelling these ancient caribou routes and hunter-gatherer settlement systems as well as the prehistoric environments that they existed in. The Wayne State University Cultural Algorithm team has been interested assisting Dr. O’Shea’s archaeological team by …


Identification Of Streptococcus Pyogenes Using Raman Spectroscopy, Ehsan Majidi Jan 2018

Identification Of Streptococcus Pyogenes Using Raman Spectroscopy, Ehsan Majidi

Wayne State University Dissertations

Despite the attention that Raman Spectroscopy has gained recently in the area of pathogen identification, the spectra analyses techniques are not well developed. In most scenarios, they rely on expert intervention to detect and assign the peaks of the spectra to specific molecular vibration. Although some investigators have used machine-learning techniques to classify pathogens, these studies are usually limited to a specific application, and the generalization of these techniques is not clear. Also, a wide range of algorithms have been developed for classification problems, however, there is less insight to applying such methods on Raman spectra. Furthermore, analyzing the Raman …


Towards Personalized Medicine Using Systems Biology And Machine Learning, Calin Voichita Jan 2013

Towards Personalized Medicine Using Systems Biology And Machine Learning, Calin Voichita

Wayne State University Dissertations

The rate of acquiring biological data has greatly surpassed our ability to interpret it. At the same time, we have started to understand that evolution of many diseases such as cancer, are the results of the interplay between the disease itself and the immune system of the host. It is now well accepted that cancer is not a single disease, but a “complex collection of distinct genetic diseases united by common hallmarks”. Understanding the differences between such disease subtypes is key not only in providing adequate treatments for known subtypes but also identifying new ones. These unforeseen disease subtypes are …


Bringing To Life An Ancient Urban Center At Monte Albán, Mexico: Exploiting The Synergy Between The Micro, Meso, And Macro Levels In A Complex System, Thaer W. Jayyousi Jan 2012

Bringing To Life An Ancient Urban Center At Monte Albán, Mexico: Exploiting The Synergy Between The Micro, Meso, And Macro Levels In A Complex System, Thaer W. Jayyousi

Wayne State University Dissertations

In this dissertation, agent-based models of emergent ancient urban centers were constructed through the use of techniques from computational intelligence, agent-based modeling, complex systems, and data-mining of existing archaeological data from the prehistoric urban center, Monte Albán. This real world application was selected because of its importance in understanding the emergence of modern economic and political systems. Specifically, Cultural Algorithms was used to evolve models of early Monte Alban, models that can then be compared with existing models of ancient and modern urban centers.

Features of a complex system were used to help interpret the archaeological data. The analysis went …