The thesis is divided into three main parts. The first section summarizes the theory of the issue. Here we are unified theoretical information about the various possibilities of different approaches. The result of this part is therefore a general summary of theoretical possible procedures of creation bone implant, where each are listed the advantages and disadvantages. The theoretical part also contains information that ultimately, in practice, the author did not use. But his idea was to create a comprehensive look at the issue from several angles. The second part uses theoretical knowledge from the previous set of information as a basis for defining the steps required to successfully manage the issues of bone 3D printing. The third part will follow the guidelines of both previous and focuses on practical making bones and subsequent evaluation method chosen. There are discussed various steps that led to the final conclusion, making bones and work is then focused on the evaluation of the success of selected procedures and recommendations for future action.

Allt fler misshandelsbrott sker i Sverige enligt Brå. För att reducera detta kan det som fångats på övervakningskameror användas i brottsutredningar, för att senare användas som bevismaterial till att döma den eller de skyldiga till brottet. Genom att optimera övervakningen kan företag använda sig av automatiserad igenkänning. Automatisering för igenkänningen av normala kontra onormala beteenden går att lösa med djupinlärning. Syftet med denna undersökning är att finna en lämplig modell som kan identifiera det onormala beteendet (till exempel ett slagsmål). Modell arkitekturen som användes under projektet var 3D ResNet, eftersom den klara av en djupare arkitektur. Ett djupare nätverk, innebär bättre prediktion av problemet. 3DResNet-34 var den modell arkitekturen som gav högst noggrannhet med 93,33%. Implementering av projektet utfördes i ramverket PyTorch. Undersökningen har visat att med           hjälp av överförd inlärning går det att återanvända kunskap från förtränade modeller och applicera dessa kunskaper på det aktuella problemet. Detta bidrar till en mer pålitligare modell med noggrann prediktion på nytt övervaknings           material. / According to Brå, more assault crimes are taking place in Sweden. To reduce this, information that was captured on surveillance cameras can be used in criminal investigations, to convict the perpetrator or perpetrators of the crime. To optimize monitoring, companies can use automation. Automation of the recognition of normal versus abnormal activities can be solved with deep learning. The purpose of this study is to find a suitable model that can identify               the abnormal activity (for example, a fight). The model architecture used during the project was 3D ResNet, because it was capable of handling deeper architectures. Having a deeper network means better prediction of the problem.           3D ResNet-34 was the model architecture that gave the highest accuracy with 93,33%. Implementation of the project was carried out in the framework of PyTorch. The study has shown that with the help of transfer learning it is possible to transfer knowledge from pre-trained models and apply this          knowledge to the current problem. This contributes to a more reliable model with accurate prediction for new surveillance footage.

INTRODUCTION: Fractures and broken bones are complications within the pediatric population that frequently occur. Many children require a prolonged immobilization of an arm or leg as a result of these injuries. Physicians often place these children in casts for several weeks to months. While casting is needed for most fractures to properly heal and recover, the two most popular casts plaster and fiberglass, can cause certain complications. Parents struggle dealing with how to bathe their children without getting the cast wet. Also, it is difficult to tell how well the child's skin beneath the cast is doing during the duration of the cast immobilization. Sometimes blood blisters or rashes can develop on the surface of the child’s skin. With the rampant development of 3D printers, the printing of 3D casts has become readily available and cheap. The biggest advantages to using 3D printed casts include them being lightweight and their ability to get wet. This ongoing feasibility study looks at the clinical effectiveness of 3D printed casts in treating children with minimally displaced radius fractures. OBJECTIVES: The main objective of this feasibility study is trying to incorporate the use of 3D printing technology to pediatric patients. Other objectives include creating, designing, and placement of 3D printed casts on patients. Determine the clinical effectiveness of 3D printed casts and ensuring the patient’s fracture healed correctly. Evaluate the skin of patients who have completed a cast immobilization in a 3D printed cast. METHODS: Patients are recruited from the Children’s National Hospital Emergency Room in Washington, D.C. If a patient meets the inclusion criteria, the Chief of Pediatric Orthopedic Surgery at Children’s National Hospital will introduce the feasibility study to both the patients and their families. Once enrolled in the study, the patient will have a 3D scan taken of their injured wrist and arm with an Artec EVA, a handheld 3D scanner. The 3D scan is taken worked through multiple software programs that create a patient-specific 3D cast. The casts are printed either by an in-house 3D printer at Children’s National or outsourced to Xometry, a company that specializes in 3D printing. The patient returns one week later from the time the scan was taken and will be removed from the temporary splint they had been placed in. The Principal Investigator or the Chief of Pediatric Orthopedic Surgery will wrap the patient’s arm with AquaLiner, a waterproof cast liner. The 3D printed cast is then placed on the patient’s arm and firmly secured with eight zip-ties. Three X-rays will be taken throughout the course of the cast immobilization that may last four to six weeks. A skin assessment tool that has a scale from zero to twelve will be used by the physicians involved to evaluate the skin of the patient post-treatment. Lastly, a QuickDash survey will be filled out by the patient before being discharged and a QuickDash score that determines percent disability will be calculated on a scale of 0-100 percent. RESULTS: One patient enrolled and completed the feasibility study. The patient’s X-rays indicated their fracture healed properly while immobilized in the 3D printed cast. A score of ten out of twelve was given based on the skin assessment tool. The QuickDash score resulted in a 6.8 percent disability. The patient stated that they would have chosen the 3D printed cast over a traditional plaster cast due to the comfortability of the cast. CONCLUSIONS: Overall, the results from the one patient that completed the study proved that 3D printed casts can be used to treat minimally displaced radius fractures. The 3D printed cast was able to keep the patient’s arm in place and protect it while the fracture healed. Much of the work put into this feasibility study was the workflow needed to create and place a 3D printed cast on a patient. The appearance and design of the cast allowed the patient to feel comfortable during the entire treatment. More patients will need to be recruited and enrolled into the study to tell whether or not this project can be moved into other medical applications.

Over the past decades, many studies have been conducted to generate in vitro tissue systems that help understanding tissue development and disease progression. Hydrogel scaffolds have been frequently used in creating such models. Self-assembling peptide hydrogels are functional in providing the cells a scaffold that supports cell proliferation, however, organoid and lumen formation remains a challenge. Hydrogels can be synthesized and modified based on the essential physiological properties, which can be achieved by altering the chemical composition of the initial material. Thus, in this study, we test the effect of the laminin-derived IKVAV motif on ultrashort self-assembling peptide in relation to cell proliferation and lumen formation in colorectal cancer stem cells. Further, we test the printability of the modified peptide. The modification of ultrashort peptide serves the purpose of providing signals to direct cell adhesion, differentiation, and lumen formation. One particular combination of peptides showed the formation of colorectal organoids containing lumen of outperforming characteristics as compared to the others, also in 3D bioprinting.

My thesis investigates automation and optimizations for occlusion filling, a problem resulting from the generation of new viewpoints in the 3D video conversion process. Image inpainting is a popular topic in image processing research. The ability to fill a region of an image in a manner that is visually pleasing is a difficult and computationally expensive task. Recently, the most successful methods have been exemplar-based, copying patches of the image from a specified source region into the region to be filled. These algorithms are designed to propagate both structure and texture into the fill region. They are brute force algorithms however, and are generally implemented as sequential algorithms to be run on the CPU. In this research, I have effectively mapped the costly portions of an exemplar-based image inpainting algorithm to the GPU. I produce equivalent inpainting results in less time by parallelizing the brute force patch searching portion of the algorithm. Furthermore, I compare the results with another recent, optimized inpainting algorithm, and apply both algorithms to the real world problem of occlusion filling in a 3D video conversion pipeline. / Graduate

L'objectif de ces travaux de thèse consiste à mettre en place des solutions algorithmiques permettant de reconstruire un modèle 3D éditable d'un environnement intérieur à l'aide d'une tablette équipée d'un capteur de profondeur.Ces travaux s'inscrivent dans le contexte de la rénovation d'intérieur. Les normes Européennes poussent à la rénovation énergétique et à la modélisation 3D des bâtiments existants. Des outils professionnels utilisant des capteurs de type LIDAR permettent de reconstruire des nuages de points de très grande qualité, mais sont coûteux et longs à mettre en œuvre. De plus, il est très difficile d'identifier automatiquement les constituants d'un bâtiment pour en exporter un modèle 3D éditable complet.Dans le cadre de la rénovation d’intérieur, il n'est pas nécessaire de disposer des informations sur l'ensemble du bâtiment, seules les principales dimensions et surfaces sont nécessaires. Nous pouvons alors envisager d'automatiser complètement le processus de modélisation 3D.La mise sur le marché de capteurs de profondeur intégrables sur tablettes, et l'augmentation des capacités de calcul de ces dernières nous permet d'envisager l'adaptation d'algorithmes de reconstruction 3D classiques à ces supports.Au cours de ces travaux, nous avons envisagé deux approches de reconstruction 3D différentes. La première approche s'appuie sur des méthodes de l'état de l'art. Elle consiste à générer un maillage 3D d'un environnement intérieur en temps réel sur tablette, puis d'utiliser ce maillage 3D pour identifier la structure globale du bâtiment (murs, portes et fenêtres). La deuxième approche envisagée consiste à générer un modèle 3D éditable en temps réel, sans passer par un maillage intermédiaire. De cette manière beaucoup plus d'informations sont disponibles pour pouvoir détecter les éléments structuraux. Nous avons en effet à chaque instant donné un nuage de points complet ainsi que l'image couleur correspondante. Nous avons dans un premier temps mis en place deux algorithmes de segmentation planaire en temps réel. Puis, nous avons mis en place un algorithme d'analyse de ces plans permettant d'identifier deux plans identiques sur plusieurs prises de vue différentes. Nous sommes alors capables d'identifier les différents murs contenus dans l'environnement capturé, et nous pouvons mettre à jour leurs informations géométriques en temps réel. / This thesis works consisted to implement algorithmic solutions to reconstruct an editable 3D model of an indoor environment using a tablet equipped with a depth sensor.These works are part of the context of interior renovation. European standards push for energy renovation and 3D modeling of existing buildings. Professional tools using LIDAR-type sensors make it possible to reconstruct high-quality point clouds, but are costly and time-consuming to implement. In addition, it is very difficult to automatically identify the constituents of a building to export a complete editable 3D model.As part of the interior renovation, it is not necessary to have information on the whole building, only the main dimensions and surfaces are necessary. We can then consider completely automating the 3D modeling process.The recent development of depth sensors that can be integrated on tablets, and the improvement of the tablets computation capabilities allows us to consider the adaptation of classical 3D reconstruction algorithms to these supports.During this work, we considered two different 3D reconstruction approaches. The first approach is based on state-of-the-art methods. It consists of generating a 3D mesh of an interior environment in real time on a tablet, then using this 3D mesh to identify the overall structure of the building (walls, doors and windows). The second approach envisaged is to generate a 3D editable model in real time, without passing through an intermediate mesh. In this way much more information is available to be able to detect the structural elements. We have in fact at each given time a complete point cloud as well as the corresponding color image. In a first time we have set up two planar segmentation algorithms in real time. Then, we set up an analysis algorithm of these plans to identify two identical planes on different captures. We are then able to identify the different walls contained in the captured environment, and we can update their geometric information in real-time.

Indiana University-Purdue University Indianapolis (IUPUI) / Rapid development of digital technology has enabled the real-time volume rendering of scientific data, in particular large microscopy data sets. In general, volume rendering techniques project 3D discrete datasets onto 2D image planes, with the generated views being transparent and having designated color that is not necessarily "real" color. Volume rendering techniques initially require designating a processing method that assigns different colors and transparency coefficients to different regions. Then based on the "viewer" and the dataset "location," the method will determine the final imaging effect. Current popular techniques include ray casting, splatting, shear warp, and texture-based volume rendering. Of particular interest is ray casting as it permits the display of objects interior to a dataset as well as render complex objects such as skeleton and muscle. However, ray casting requires large memory and suffers from longer processing time. One way to address this is to parallelize its implementation on programmable graphic processing hardware. This thesis proposes a GPU based ray casting algorithm that can render a 3D volume in real-time application. In addition, to implementing volume rendering techniques on programmable graphic processing hardware to decrease execution times, 3D image segmentation techniques can also be utilized to increase execution speeds. In 3D image segmentation, the dataset is partitioned into smaller sized regions based on specific properties. By using a 3D segmentation method in volume rendering applications, users can extract individual objects from within the 3D dataset for rendering and further analysis. This thesis proposes a 3D segmentation algorithm with combinatorial map that can be parallelized on graphic processing units.

Eastern newts (Notophthalmus viridescens) are a ubiquitous member of eastern North America’s caudate fauna. Unlike the typical amphibian, their life cycle is split into three phases instead of two, commonly called a triphasic life cycle. The larvae of N. viridescens are fully aquatic, eventually metamorphosing to become terrestrial juveniles called efts. Upon sexual maturity, the eft will metamorphose into a semi-aquatic adult whose external morphology resembles other aquatic salamander species. The eastern newt has predominantly been described by its external traits, namely color changes and lateral tail compression, rather than the musculoskeletal system and anatomy. Since these salamanders occupy different ecological niches (aquatic vs. terrestrial) throughout their lives and likely experience different forces acting on their skeletons, they provide a unique opportunity to study internal changes across ontogeny and ecology. We hypothesize that differences in buoyancy, torsion, and locomotion are expected to result in morphological shape changes across the life stages of the eastern newt’s skeleton. Using image data generated on a SkyScan 1273 micro-computed tomography (µCT) scanner (Bruker), 3D shape analyses will quantify shape differences between individual bones and test the hypothesis. Three-dimensional digital models of each bone of interest will be rendered from the scans in Dragonfly (Object Research Systems). Each 3D model is loaded into SlicerMorph (3DSlicer), where 3D geometric morphometrics is conducted for each bone to test for potential shape differences between each life stage. Our results support a shape difference between eft and adult in particular bones and conserved shape across ontogeny in other bones. Differences in shape are associated with a difference in functional demand across ecological niches.

Lower back pain and intervertebral disc degeneration represent a global socio-economical problem affecting 266 million people annually, always increasing due to aging of the population. No restorative treatments are available. In case of chronic degeneration, surgical operation with spinal fusion or total disc replacement represents the best alternative. This leads to pain relief but reduces the patient’s mobility. Moreover, follow-ups and re-intervention due to weak osteointegration are common consequences of currently used metal prostheses. For this reason, there is an urgent need to develop customized regenerative approaches aimed at the restoration of IVD function, as well as the optimization of osteointegration in actual vertebral prostheses by creating hybrid metal implants with infill materials to better induce bone ingrowth. In this work, tissue engineering-based approaches have been exploited by tuning the remarkable properties of silk fibroin for two purposes, disc restoration via in situ 3D printing technique, and improvement of osteointegration of vertebral prostheses. In situ 3D printing is the most promising strategy for the development of a personalized medicine approach aimed at the restoration of IVD. However, silk fibroin application as pristine ink in 3D printing technique is hindered by its low viscosity. For this reason, the aim of the first part of the work has been the design and development of silk fibroin-based inks in situ applications, overcoming its intrinsic limitations. Specifically, a covalent crosslinking process consisting of a pre-photo-crosslinking prior to printing and in situ enzymatic crosslinking was designed. Two different silk fibroin molecular weights were characterized. We proved that despite the use of low concentration silk solutions, the synergistic effect of the covalent bonds with the shear forces applied in the nozzle enhanced silk secondary structure shift toward β-sheets conformation. The resultant hydrogels exhibited good mechanical properties, stability over time, and resistance to enzymatic degradation over 14 days, with no significant changes over time in their secondary structure and swelling behavior. The designed process was tunable and versatile, leading to good shape fidelity and printing resolutions, making real the application of silk fibroin-based inks for in situ applications. The results obtained represent an important step for further studies on the mimicry of the whole IVD structure. 2 In the second part of the work, silk fibroin has been evaluated as candidate infill material for metal prostheses to improve bone ingrowth and osteointegration. In two independent works, silk fibroin-based foams and methacrylate silk fibroin sponges were biologically characterized and the differentiation of bone marrow-derived human mesenchymal stem cells (hBM-MSCs) toward osteogenic phenotype was studied. Silk fibroin foams have been demonstrated to induce and support cells adhesion, migration, and differentiation, and to induce early mineralization phase since day 7 during the differentiative culture. Methacrylate silk fibroin foams have been fabricated with different photo-initiator concentrations and in presence/absence of a porogen. The impact of the composition on the pore size, mechanical properties, and stem cells differentiation was deeply investigated. We demonstrated that despite all the conditions well-supported cells differentiation, the lowest photo-initiator concentration in combination with the porogen used enhanced osteogenic differentiation as confirmed by gene expression tests.

Video coding systems based on 3D wavelet transforms offer several advantages over traditional hybrid video coders. This thesis proposes two 3D wavelet-based video-coding approaches. In the first approach, motion compensation with redundant-wavelet multihypothesis, in which multiple predictions that are diverse in transform phase contribute to a single motion estimate, is deployed into the fully scalable MC-EZBC video coder. The bidirectional motion-compensated temporaliltering process of MC-EZBC is adapted to the redundant-wavelet domain, wherein transform redundancy is exploited to generate a phase-diverse multihypothesis prediction of the true temporal filtering. In the second approach, a video coder is proposed that does not perform motion compensation explicitly, instead relying on the motion-selective characteristics of the 3D dual-tree discrete wavelet transform to isolate moving features. The transform coefficients are coded with binary set-partitioning using k-d trees in an algorithm that exploits within-subband spatiotemporal coherency as well as cross-subband correlation to achieve efficient coding.