Diagnosis of Lung Disorder Using Immune Genetic Algorithm and Fuzzy logic to Handle Incertitude

In this paper, we present an immune based fuzzy-logic approach for computer-aided diagnosis scheme in medical imaging. The scheme applies to lung CT images and to detect and classify lung nodules. Classification of lung tissue is a significant and challenging task in any computer aided diagnosis system. This paper presents a technique for classification of lung tissue from computed tomography of the lung using the Gaussian interval type-2 fuzzy logic system. The type-2 Gaussian membership functions (T2MFs) and their footprint of uncertainty (FOU) are tuned by immune, genetic algorithm, which is the combination of immune genetic algorithm (GA) and local exploration operator. An immune, genetic algorithm estimates the parameters of the type-2 fuzzy membership function (T2MF). By using immune, genetic algorithm, converging speed is increased. The proposed local exploration operator helps in finding the best Gaussian distribution curve of a particular feature which improves the efficiency and accuracy of the diagnosis system

An improved data classification framework based on fractional particle swarm optimization

Particle Swarm Optimization (PSO) is a population based stochastic optimization technique which consist of particles that move collectively in iterations to search for the most optimum solutions. However, conventional PSO is prone to lack of convergence and even stagnation in complex high dimensional-search problems with multiple local optima. Therefore, this research proposed an improved Mutually-Optimized Fractional PSO (MOFPSO) algorithm based on fractional derivatives and small step lengths to ensure convergence to global optima by supplying a fine balance between exploration and exploitation. The proposed algorithm is tested and verified for optimization performance comparison on ten benchmark functions against six existing established algorithms in terms of Mean of Error and Standard Deviation values. The proposed MOFPSO algorithm demonstrated lowest Mean of Error values during the optimization on all benchmark functions through all 30 runs (Ackley = 0.2, Rosenbrock = 0.2, Bohachevsky = 9.36E-06, Easom = -0.95, Griewank = 0.01, Rastrigin = 2.5E-03, Schaffer = 1.31E-06, Schwefel 1.2 = 3.2E-05, Sphere = 8.36E-03, Step = 0). Furthermore, the proposed MOFPSO algorithm is hybridized with Back-Propagation (BP), Elman Recurrent Neural Networks (RNN) and Levenberg-Marquardt (LM) Artificial Neural Networks (ANNs) to propose an enhanced data classification framework, especially for data classification applications. The proposed classification framework is then evaluated for classification accuracy, computational time and Mean Squared Error on five benchmark datasets against seven existing techniques. It can be concluded from the simulation results that the proposed MOFPSO-ERNN classification algorithm demonstrated good classification performance in terms of classification accuracy (Breast Cancer = 99.01%, EEG = 99.99%, PIMA Indian Diabetes = 99.37%, Iris = 99.6%, Thyroid = 99.88%) as compared to the existing hybrid classification techniques. Hence, the proposed technique can be employed to improve the overall classification accuracy and reduce the computational time in data classification applications

Astigmatism and Pseudoaccommodation in Pseudophakic Eyes

noAdvanced IOLs with circumferential zones of different power provide pseudoaccommodation. We investigated the potential for power variation with meridian, namely astigmatism, to provide pseudo-accommodation. With appropriate power and axis orientations, acceptable pseudo-accommodation can be achieved

Image similarity in medical images

Recent experiments have indicated a strong influence of the substrate grain orientation on the self-ordering in anodic porous alumina. Anodic porous alumina with straight pore channels grown in a stable, self-ordered manner is formed on (001) oriented Al grain, while disordered porous pattern is formed on (101) oriented Al grain with tilted pore channels growing in an unstable manner. In this work, numerical simulation of the pore growth process is carried out to understand this phenomenon. The rate-determining step of the oxide growth is assumed to be the Cabrera-Mott barrier at the oxide/electrolyte (o/e) interface, while the substrate is assumed to determine the ratio β between the ionization and oxidation reactions at the metal/oxide (m/o) interface. By numerically solving the electric field inside a growing porous alumina during anodization, the migration rates of the ions and hence the evolution of the o/e and m/o interfaces are computed. The simulated results show that pore growth is more stable when β is higher. A higher β corresponds to more Al ionized and migrating away from the m/o interface rather than being oxidized, and hence a higher retained O:Al ratio in the oxide. Experimentally measured oxygen content in the self-ordered porous alumina on (001) Al is indeed found to be about 3% higher than that in the disordered alumina on (101) Al, in agreement with the theoretical prediction. The results, therefore, suggest that ionization on (001) Al substrate is relatively easier than on (101) Al, and this leads to the more stable growth of the pore channels on (001) Al

Novel optimisation methods for numerical inverse problems

Inverse problems involve the determination of one or more unknown quantities usually appearing in the mathematical formulation of a physical problem. These unknown quantities may be boundary heat flux, various source terms, thermal and material properties, boundary shape and size. Solving inverse problems requires additional information through in-situ data measurements of the field variables of the physical problems. These problems are also ill-posed because the solution itself is sensitive to random errors in the measured input data. Regularisation techniques are usually used in order to deal with the instability of the solution. In the past decades, many methods based on the nonlinear least squares model, both deterministic (CGM) and stochastic (GA, PSO), have been investigated for numerical inverse problems. The goal of this thesis is to examine and explore new techniques for numerical inverse problems. The background theory of population-based heuristic algorithm known as quantum-behaved particle swarm optimisation (QPSO) is re-visited and examined. To enhance the global search ability of QPSO for complex multi-modal problems, several modifications to QPSO are proposed. These include perturbation operation, Gaussian mutation and ring topology model. Several parameter selection methods for these algorithms are proposed. Benchmark functions were used to test the performance of the modified algorithms. To address the high computational cost of complex engineering optimisation problems, two parallel models of the QPSO (master-slave, static subpopulation) were developed for different distributed systems. A hybrid method, which makes use of deterministic (CGM) and stochastic (QPSO) methods, is proposed to improve the estimated solution and the performance of the algorithms for solving the inverse problems. Finally, the proposed methods are used to solve typical problems as appeared in many research papers. The numerical results demonstrate the feasibility and efficiency of QPSO and the global search ability and stability of the modified versions of QPSO. Two novel methods of providing initial guess to CGM with approximated data from QPSO are also proposed for use in the hybrid method and were applied to estimate heat fluxes and boundary shapes. The simultaneous estimation of temperature dependent thermal conductivity and heat capacity was addressed by using QPSO with Gaussian mutation. This combination provides a stable algorithm even with noisy measurements. Comparison of the performance between different methods for solving inverse problems is also presented in this thesis

카이랄 나노구조의 플라즈몬 커플링을 기반한 원편광 이색성 변조

학위논문(박사) -- 서울대학교대학원 : 공과대학 재료공학부, 2022.2. 남기태.카이랄 메타 물질은 뛰어난 광 물질 상호 작용으로 인하여 나노 광자 분야에서 큰 관심을 받아왔다. 다년간의 연구를 통하여 최첨단 리소그래피 기술과 분자 조립 스캐폴드를 사용하여 카이랄 나노구조가 제작되어 왔다. 기하학적 비대칭성을 지니는 카이랄 무기 금속 나노 물질은 대칭성을 가지는 나노 물질에서 얻을 수 없었던 독특한 물리적 현상을 나타낼 수 있다. 카이랄 나노 구조는 음의 굴절률, 분자 감지 및 광대역 원형 편광과 같은 광학적 효과를 나타내기 위해 사용될 수 있다. 이러한 카이랄 메타 물질의 뛰어난 광학 특성을 실제 장치에 통합하기 위해서는 섬세하게 설계된 광학적 성질을 가지는 카이랄 구조를 달성하는 것이 필요하다. 그러나 고가의 제조비용 및 설비, 복잡한 제조 과정 및 제한된 해상도로 인해 카이랄 메타 물질을 실제 장치로 통합하는 데 제한이 있어왔다. 이러한 한계를 극복하기 위해서는 카이랄 나노 구조 제어를 위한 유연한 방법론을 개발하는 것이 요구된다. 본 학위 연구 에서는 펩타이드를 이용한 나노 입자 형태의 다양화와 나노 구조에서의 플라즈몬 커플링을 이용한 광학적 반응의 추가적인 조절이 앞서 언급한 한계를 해결하기 위한 유망한 대안이 될 수 있음을 제안한다. 본 학위 논문은 카이랄 나노 구조의 발달에 대한 이해와 조절을 통해 플라즈몬 커플링을 이용하여 카이랄 광학 응답을 조절할 수 있는 플랫폼을 제시한다. 생체분자를 이용한 플라즈몬 나노 입자의 콜로이드 합성에 대한 최근 연구결과는 합성 과정에 관여하는 카이랄성 인코더인 분자를 변경함으로써 새로운 형태와 광학적 특성을 가진 나노입자를 합성할 수 있음을 시사한다. 또한 단일 플라즈몬 입자의 광학 응답은 플라즈몬 커플링을 사용하여 증폭되고 민감하게 변조될 수 있다. 여러 플라즈몬 나노 입자가 인접할 경우, 입자 공명의 혼성화가 유도되어 공명을 크게 변화시킨다. 플라즈몬 나노 구조의 형태와 카이랄성을 제어하기 위한 새로운 전략을 수립하기 위하여, 우리는 먼저 생체분자에 의해 유도되는 무기 카이랄성에 초점을 맞추었다. 무기 표면에서의 원자 왜곡 또는 거시적 재구성을 통한 카이랄성의 진화에 대한 기존 연구는 카이랄 나노 구조 제어를 위한 새로운 전략 수립에 중요한 통찰력을 제공한다. 본 학위논문에서는 카이랄 광학 반응의 이해와 조절을 단일 나노 입자와 시스템적 제어의 두 가지 관점에서 소개한다. 나노 재료 공학의 발전으로 나노 규모에서 정확한 형태학적 제어가 가능한 콜로이드 합성 방법이 개발되었다. 다양한 할로겐화물 이온, 금속 이온 및 유기 분자를 흡착제로 사용하면 특정 Miller 지수로 결정면을 부동태화하여 결정면과 나노입자 형태를 손쉽게 제어할 수 있다. 또한 종자 매개 방법은 높은 Miller-index 결정면을 높은 균일도로 생성할 수 있으므로 나노 입자의 형태를 제어하는 중요한 전략으로 사용된다. 우리는 합성에 첨가하는 유기 분자를 변경하여 금 나노 입자의 성장 및 카이랄성 진화에 대한 광범위한 이해를 제공한다. 이를 위하여 γ-글루타밀시스테인(γ-Glu-Cys) 및 시스테이닐글리신(Cys-Gly) 을 사용하여 합성된 금 나노 입자의 성장 경로와 키랄성 진화가 결정학적 관점에서 분석되었다. γ-Glu-Cys을 이용하여 합성된 금 나노 입자의 경우 돌출된 카이랄 날개를 가지는 정육면체 구조로 발달한다. 반면에, Cys-Gly을 이용하여 합성된 나노입자의 경우 타원형의 공동 구조를 가진 마름모꼴 12면체로 발달하며, 이로 인해 두 나노 입자는 서로 다른 카이랄 광학 반응을 보인다. 시간에 따른 나노 입자의 성장 분석을 통해 γ-Glu-Cys와 Cys-Gly가 서로 다른 중간 형태를 지니며 생성한다는 것을 알 수 있었다. γ-Glu-Cys는 오목한 육팔면체 모양의 중간체를 유도하는 반면 Cys-Gly는 오목한 마름모꼴 십이면체의 중간체를 보인다. 이러한 결과는 펩타이드와 금 표면 간의 상호 작용을 이해함으로써 카이랄 구조와 그에 따른 광학 반응을 조절할 수 있음을 시사한다. 생체 분자를 이용한 카이랄 나노구조의 합성은 주로 플라즈몬 물질에서 연구되어 왔지만, 촉매 활성을 지녀 카이랄 촉매로 사용될 수 있는 카이랄 금속 산화물을 합성하려는 시도 또한 카이랄 물질의 응용 확대를 위한 새로운 방향으로 제시되고 있다. 생체 분자를 이용한 카이랄 금속 산화물 합성에서의 기존 연구는 단일 아미노산에 국한되어 있지만, 카이랄성 발달을 이해하고 확장 가능한 합성 전략을 수립하기 위해서는 펩타이드로의 서열 확장이 요구된다. 본 연구에서는 Tyr-Tyr-Cys 펩타이드를 서열확장을 위한 리간드로 선택하여, 코발트 산화물에서 펩타이드를 이용한 카이랄성 발현을 탐구하였다. 펩타이드 리간드를 이용하여 합성된 카이랄 코발트 산화물 나노 입자는 자외선 및 가시광선 영역에서 0.01의 뛰어난 비대칭 인자를 나타냈다. 또한, 2D NMR 분광 분석을 통해 나노 입자 표면의 펩타이드 리간드의 3차원 입체구조를 규명하였다. 또한 펩타이드 리간드의 시퀀스에 따른 카이랄 코발트 산화물 나노 입자의 발달을 분석하여 Tyr-Tyr-Cys 리간드의 싸이올 그룹과 카복실 그룹이 카이랄성 발달에 중요한 역할을 담당함을 규명하였다. 본 연구 결과는 무기 결정에 카이랄성을 발현하는 펩타이드의 역할이 상호 작용하는 물질에 따라 달라질 수 있으며, 카이랄 광학 특성의 변화를 야기할 수 있음을 시사한다. 단일 플라즈몬 나노 입자의 광학 신호는 플라즈몬 커플링을 통하여 증폭되고 민감하게 제어될 수 있다. 여러 개의 플라즈몬 나노 입자가 인접할 경우, 입자 공명의 혼성화가 일어나 공명을 크게 변화시킨다. 이러한 맥락에서, 본 연구에서는 플라즈몬 커플링을 카이랄 플라즈몬 나노 입자에 적용하여 카이랄 광학 특성을 제어하고자 하였다. 이를 위하여 카이랄 금 나노 입자를 기판에 코팅하고 나노 크기의 플라즈몬 금속 층을 증착하여 메타 물질을 제작하였다. 플라즈몬 결합으로 인한 광학 특성의 변화는 투과 기반 및 확산 반사 기반 원편광 이색성 (cirular dichroism, CD) 분광법을 통해 분석되었다. 카이랄 금속 나노 입자 기반 메타 물질의 광학적 분석을 통해 CD 스펙트럼의 피크 위치, 세기 및 부호가 플라즈몬 커플링에 의해 변화함을 알 수 있었다. 또한, 플라즈몬 커플링에 의해 생성된 모드는 나노구조체의 크기, 거리 및 주변 굴절률에 따라 크게 변화하였다. 더 나아가, 카이랄 금 나노 입자에 실리카 쉘의 플라즈몬 나노입자의 광학 특성 및 안정성의 제어가 가능함을 규명하였다. 본 학위 연구에서는 나노 입자의 카이랄성 발달에 펩타이드 리간드가 미치는 역할을 이해함으로써 단일 나노 입자 수준에서 CD 신호의 제어를 달성하였다. 또한 플라즈몬 커플링을 사용하여 카이랄 나노 구조의 광학적 특성을 조절하는 방법론이 확립되었다. 본 연구를 통하여 개발된 카이랄 나노 구조에서 광학 특성의 조절을 위한 방법론은 카이랄 메타 물질을 실용적인 광학 장치로 통합하는 것을 용이하게 할 것으로 기대된다.Chiral metamaterials have been actively pursued in the field of nanophotonics due to their exceptional light-matter interactions. For decades, numerous attempts have been conducted to fabricate chiral nanostructure using state-of-the-art lithography techniques and molecular-assembly scaffolds. Possessing this geometric property, inorganic metal nanomaterials could exhibit fascinating physical phenomena which was difficult to be achieved in symmetric nanomaterials. Chiral nanostructures have greatly expanded the design to demonstrate chiroptic effects such as a negative refractive index, sensitive chiral sensing, and broad-band circular polarizer. In order to integrate the fascinating properties of chiral metamaterials into practical devices, it is necessary to achieve precisely defined chiral morphologies and chiroptic properties. However, the requirement for expensive facilities, the complexity of the process, and the limited resolution had restricted the translation of chiral metamaterials into real devices. Therefore, developing flexible methodologies for nanostructure control is important to address these limitations and provide new directions. Through this study, we propose that the diversification of nanoparticle morphology using peptide molecules and further modulation of the optical response utilizing plasmonic coupling of nanostructures can be a promising alternative to solve the above-mentioned limitations. In this thesis, we present a platform that can modulate the chiroptic response using plasmon coupling through understanding and regulation of the development of chiral nanostructures. Recent study on the colloidal synthesis of plasmonic nanoparticles using biomolecules suggests that nanoparticles with novel morphology and optical property can be achieved by altering molecules, which are chirality encoders, involved during the synthesis. In addition, the optical response of a single plasmonic particle can be amplified and sensitively modulated using plasmon coupling. When several nanoscale plasmonic particles are adjacent to each other, hybridization of particle resonance is induced, which significantly changes the resonance. To establish new strategies for controlling the morphology and chirality of plasmonic nanostructures, we have first studied previous studies on bio-inspired pathways for complex nanostructures, focusing on the inorganic chirality induced by biomolecules in Chapter 2. Importantly, the interactions at the interface between biomolecules and inorganic surfaces provide an important insight into the evolution of chirality through atomic distortion or macroscopic reconstruction. Chapter 3 describes the experimental procedures, and Chapter 4, 5, and 6 describe the understanding and modulation of the chiroptic response from the two perspectives of single nanoparticles and systemic control. Advances in nanomaterial engineering have enabled the development of colloidal synthesis methods for precise morphological control at the nanoscale. The use of various halide ions, metal ions and organic molecules as adsorbates can control the crystal facet and nanoparticle morphology by passivating the crystal facet with a specific Miller index. In addition, the seed-mediated method can synthesize high-Miller-index crystal facets with high uniformity, and thus is being used as an important strategy for controlling NP morphology. In this thesis, we have provided a broad understanding of the growth and chirality evolution in gold NPs by adjusting the type of additive molecules. We have analyzed the growth pathway and chirality evolution of the γ-glutamylcysteine- (γ-Glu-Cys-) and cysteinylglycine- (Cys-Gly-) directed gold NPs from a crystallographic perspective. Gold NPs developed into a cube-like structure with protruding chiral wings in the presence of γ-Glu-Cys, whereas the NPs synthesized with Cys-Gly exhibited a rhombic dodecahedron-like outline with elliptical cavity structures, showing different chiroptic responses. Through time-dependent analysis, we reported that γ-Glu-Cys and Cys-Gly generate different intermediate morphologies. γ-Glu-Cys induced concave hexoctahedra-shaped intermediate, whereas Cys-Gly showed concave rhombic dodecahedra-shaped intermediate. These results showed that the chiral structure and resulting chiroptic response can be modulated through understanding the interaction between peptides and gold surfaces. Molecule-directed synthesis of chiral nanostructure has been mainly studied in plasmonic materials, but attempts to synthesize chiral metal oxides that can be used as chiral catalysts due to their catalytic activity has been suggested as a new direction for expanding the application of chiral materials. Existing studies on the synthesis of chiral metal oxide using molecule have been limited to single amino acids, but sequence expansion with peptides is required to understand the chirality evolution and achieve a scalable synthetic strategy. In this thesis, Tyr-Tyr-Cys tripeptide including tyrosine and cysteine were selected as peptide ligands and the role of peptide in developing chirality in cobalt oxide was explored. Synthesized chiral cobalt oxide nanoparticles showed a g-factor of 0.01 in the UV–visible region. In addition, the 3D conformation of the peptide ligand on the nanoparticle surfaces was identified by 2D NMR spectroscopy analysis. Furthermore, the sequence effect of Tyr-Tyr-Cys developing chiral cobalt oxide was analyzed, demonstrating that the thiol group and carboxyl group of the Tyr-Tyr-Cys ligand played an important role in chirality evolution. This results suggest that the role of the peptides can vary depending on the interacting material, leading to further variability in chiroptical properties. The optical signal of a single plasmonic particle can be amplified and sensitively controlled using plasmon coupling. When several nanoscale plasmonic particles are adjacent to each other, hybridization of particle resonance occurs, which significantly changes the resonance. In this context, plasmonic coupling which has been mainly studied in achiral plasmon structures, was applied to chiral plasmonic nanoparticles to control chiroptical properties. In this thesis, we demonstrated the fabrication of metamaterial by coating chiral gold nanoparticles on a substrate and depositing a nanoscale plasmonic metal layer. In order to investigate changes in optical properties due to plasmon coupling, transmission-based and diffuse reflectance circular dichroism (CD) spectroscopy were utilized. Through this, it was confirmed that the resonance position, magnitude, and sign of the CD spectrum were changed by plasmon coupling. In addition, the coupled plasmon mode was significantly changed according to the dimension, distance, and refractive index of the nanostructure. Furthermore, synthesis of chiral gold-silica core-shell NPs enables versatile control of the structure and properties of plasmonic nanoparticles, facilitating their application to tailored plasmon coupling. In conclusion, by understanding the role of peptides in nanoparticle development, CD manipulation has been achieved at the single nanoparticle level. In addition, a methodology for modulating the optical properties of chiral nanostructures using plasmon coupling has been established. We believe the development of versatile methodology for modulation of the chiroptical response in chiral nanostructures ultimately facilitate integration of the chiral metamaterials into practical optical devices.Chapter 1. Introduction 1 1.1 Chirality in Nature 1 1.2 Chiral Plasmonic Nanostructure 9 1.3 Objective of Thesis 21 Chapter 2. Fabrication of Chiral Inorganic Nanostructure and Its Optical Properties 24 2.1 Fabrication of Chiral Nanostructures using Hard Approach 24 2.2 Biomolecule-Directed Chiral Nanostructure 29 2.2.1 Biomolecule-Conjugated Inorganic Nanoparticles 29 2.2.2 Chirality Development by Biomolecule-Induced Local Distortion 36 2.2.3 Biomolecule-Directed Chiral Morphology 44 Chapter 3. Experimental Procedures 62 3.1 Synthesis of Chiral Gold Nanoparticles 62 3.2 Synthesis of Chiral Cobalt Oxide Nanoparticles 64 3.3 Synthesis of Chiral Gold-Silica Core-Shell Nanoparticles 66 3.4 Optical Characterization of Chiral Nanostructures 67 Chapter 4. Dipeptide-Directed Chiral Gold Nanoparticles 69 4.1 Introduction 69 4.2 Solution-Based Synthesis of Dipeptide-Directed Chiral NPs 72 4.3 Morphology Analysis of γ-Glu-Cys- and Cys-Gly-directed NPs 79 4.4 Time-Dependent Analysis of Chiral Morphology Development 83 4.5 Concentration-Dependent Chiral Morphology and Chiroptical Responses 91 4.6 Sequence Effects 101 4.7 Conclusion 102 Chapter 5. Peptide-Directed Chiral Cobalt Oxide Nanoparticle 103 5.1 Introduction 103 5.2 Synthesis of Chiral Cobalt Oxide Nanoparticles using Tyr-Tyr-Cys 107 5.3 Effect of Synthetic Parameters on Chirality Development of Chiral Cobalt Oxide Nanoparticles 114 5.4 3D Conformation of Tyr-Tyr-Cys Ligand 120 5.5 Sequence Effect of the Tyr-Tyr-Cys 125 5.6 Magnetic Circular Dichroism in Chiral Cobalt Oxide Nanoparticles. 129 5.7 Conclusion 134 Chapter 6. Circular Dichroism Manipulation based on Plasmonic Coupling of Chiral Nanostructures 136 6.1 Introduction 136 6.2 Chiroptical Property of Helicoid-Based Plasmonic Nanostructure 138 6.3 Effect of Chiral Gap Structure 145 6.4 Spectral Manipulation through Structural Parameter Control 149 6.5 Synthesis of Chiral Gold-Silica Core-Shell Nanoparticles 151 6.6 Conclusion 154 Chapter 7. Concluding Remarks 155 References 159박

Innovative techniques to devise 3D-printed anatomical brain phantoms for morpho-functional medical imaging

Introduction. The Ph.D. thesis addresses the development of innovative techniques to create 3D-printed anatomical brain phantoms, which can be used for quantitative technical assessments on morpho-functional imaging devices, providing simulation accuracy not obtainable with currently available phantoms. 3D printing (3DP) technology is paving the way for advanced anatomical modelling in biomedical applications. Despite the potential already expressed by 3DP in this field, it is still little used for the realization of anthropomorphic phantoms of human organs with complex internal structures. Making an anthropomorphic phantom is very different from making a simple anatomical model and 3DP is still far from being plug-and-print. Hence, the need to develop ad-hoc techniques providing innovative solutions for the realization of anatomical phantoms with unique characteristics, and greater ease-of-use. Aim. The thesis explores the entire workflow (brain MRI images segmentation, 3D modelling and materialization) developed to prototype a new complex anthropomorphic brain phantom, which can simulate three brain compartments simultaneously: grey matter (GM), white matter (WM) and striatum (caudate nucleus and putamen, known to show a high uptake in nuclear medicine studies). The three separate chambers of the phantom will be filled with tissue-appropriate solutions characterized by different concentrations of radioisotope for PET/SPECT, para-/ferro-magnetic metals for MRI, and iodine for CT imaging. Methods. First, to design a 3D model of the brain phantom, it is necessary to segment MRI images and to extract an error-less STL (Standard Tessellation Language) description. Then, it is possible to materialize the prototype and test its functionality. - Image segmentation. Segmentation is one of the most critical steps in modelling. To this end, after demonstrating the proof-of-concept, a multi-parametric segmentation approach based on brain relaxometry was proposed. It includes a pre-processing step to estimate relaxation parameter maps (R1 = longitudinal relaxation rate, R2 = transverse relaxation rate, PD = proton density) from the signal intensities provided by MRI sequences of routine clinical protocols (3D-GrE T1-weighted, FLAIR and fast-T2-weighted sequences with ≤ 3 mm slice thickness). In the past, maps of R1, R2, and PD were obtained from Conventional Spin Echo (CSE) sequences, which are no longer suitable for clinical practice due to long acquisition times. Rehabilitating the multi-parametric segmentation based on relaxometry, the estimation of pseudo-relaxation maps allowed developing an innovative method for the simultaneous automatic segmentation of most of the brain structures (GM, WM, cerebrospinal fluid, thalamus, caudate nucleus, putamen, pallidus, nigra, red nucleus and dentate). This method allows the segmentation of higher resolution brain images for future brain phantom enhancements. - STL extraction. After segmentation, the 3D model of phantom is described in STL format, which represents the shapes through the approximation in manifold mesh (i.e., collection of triangles, which is continuous, without holes and with a positive – not zero – volume). For this purpose, we developed an automatic procedure to extract a single voxelized surface, tracing the anatomical interface between the phantom's compartments directly on the segmented images. Two tubes were designed for each compartment (one for filling and the other to facilitate the escape of air). The procedure automatically checks the continuity of the surface, ensuring that the 3D model could be exported in STL format, without errors, using a common image-to-STL conversion software. Threaded junctions were added to the phantom (for the hermetic closure) using a mesh processing software. The phantom's 3D model resulted correct and ready for 3DP. Prototyping. Finally, the most suitable 3DP technology is identified for the materialization. We investigated the material extrusion technology, named Fused Deposition Modeling (FDM), and the material jetting technology, named PolyJet. FDM resulted the best candidate for our purposes. It allowed materializing the phantom's hollow compartments in a single print, without having to print them in several parts to be reassembled later. FDM soluble internal support structures were completely removable after the materialization, unlike PolyJet supports. A critical aspect, which required a considerable effort to optimize the printing parameters, was the submillimetre thickness of the phantom walls, necessary to avoid distorting the imaging simulation. However, 3D printer manufacturers recommend maintaining a uniform wall thickness of at least 1 mm. The optimization of printing path made it possible to obtain strong, but not completely waterproof walls, approximately 0.5 mm thick. A sophisticated technique, based on the use of a polyvinyl-acetate solution, was developed to waterproof the internal and external phantom walls (necessary requirement for filling). A filling system was also designed to minimize the residual air bubbles, which could result in unwanted hypo-intensity (dark) areas in phantom-based imaging simulation. Discussions and conclusions. The phantom prototype was scanned trough CT and PET/CT to evaluate the realism of the brain simulation. None of the state-of-the-art brain phantoms allow such anatomical rendering of three brain compartments. Some represent only GM and WM, others only the striatum. Moreover, they typically have a poor anatomical yield, showing a reduced depth of the sulci and a not very faithful reproduction of the cerebral convolutions. The ability to simulate the three brain compartments simultaneously with greater accuracy, as well as the possibility of carrying out multimodality studies (PET/CT, PET/MRI), which represent the frontier of diagnostic imaging, give this device cutting-edge prospective characteristics. The effort to further customize 3DP technology for these applications is expected to increase significantly in the coming years

Air Force Institute of Technology Research Report 2020

This Research Report presents the FY20 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document