This thesis contains basic theoretical information about SVM-based image segmentation and data classification. Basic information about 3D Slicer software are presented. Aspects of medical images segmentation are described. Workplan and implemetation of SVM method for MRI segmentation in 3D Slicer sofware as extension module is created. SVM method is compared with simple segmentation algorithms included in 3D Slicer. Quality of segmentation, based on SVM, tested on real subjects is experimentaly demonstrated.

Self-oscillating synthetic vocal fold (VF) models are often used to study human voice production. In this thesis, a method for fabricating multi-layer self-oscillating synthetic VF models using silicone 3D printing is presented. Multi-material 3D printing enables faster fabrication times with more complex geometries than traditional casting methods and builds a foundation for producing VF models with potentially more life-like geometries, materials, and vibratory characteristics. The printing method in this study used a custom dual extruder and slicing software to print UV-curable liquid silicone into a gel-like support matrix. The extruder was fabricated using high-torque stepper motors with high resolution leadscrews for precise extrusion and retraction. The custom slicing software accounted for challenges with printing a low-viscosity uncured silicone and was capable of allowing the user to visually observe the effects of print settings on print paths before finalizing the g-code. Three validation tests were conducted to demonstrate the 3D printer’s ability to print ultra-soft silicone with the desired range of stiffness, change between materials quickly, and print a material stiffness gradient. Two types of VF models were printed in this study, a previously-designed model with multiple distinct layers (“EPI” model), and the same model but with a vertical stiffness gradient (VSG) in the superficial lamina propria layer. The EPI model was chosen to demonstrate the ability to 3D print a multi-layer model, and the VSG model was chosen to demonstrate the ability to print multi-material VFs with geometric and material properties that are difficult to fabricate using traditional casting methods. Sixteen VFs (i.e., eight pairs) of each model type were printed, and their vibratory responses were recorded, including onset pressure, frequency, and glottal width. A micro-CT scanner was used to evaluate the external geometric accuracy of the models. One-centimeter cubes were 3D printed and tensile tested to characterize the material properties of each set of VF models. The material and phonatory properties of both the EPI and VSG VF models were found to be comparable to human data and to previous data acquired using synthetic VF models fabricated via other methods. In this thesis, the 3D printing methodology is summarized, the setup and results of the validation and VF model tests are reported and discussed, and recommendations for future work are provided.

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The viability of using a slicer based integral field spectrograph (IFS) for high contrast observations has been under scrutiny due to the belief that the one dimensional coherence that persists along the slice to the point of sampling at the detector will cause the creation of secondary speckles that will not have the same characteristics as normal speckles, thus stopping us from calibrating them out. It has also been previously assumed that a suitably low differential wavefront error when moving slice to slice was not guaranteed by design. It was for these reasons that slicer based IFSs were not selected for the current generation of planet finding instruments. As part of the EPICS (Exo Planet Imaging Camera and Spectrograph for the E-ELT) design study it was decided that slicers should be re-investigated due to results from on sky observations suggesting these limitations did not exist. The purpose of this thesis was to determine whether there was validity to the concerns mentioned above and therefore to answer the question; Would implementing a slicer based integral field spectrograph limit the achievable contrast of an instrument designed for the direct detection of exoplanets? Chapter 1 gives a brief introduction into the field of exoplanet research. Charpter 2 describes the noise limiting direct detection of exoplanets and the ways to get around it. Chapter 3 gives an overview of the two types of IFS under investigation by the EPICS consortium. Chapter 4 looks into details of the EPICS instrument and the IFS design study that came about. Chapter 5 shows simulations performed for the aim of achieving better contrasts via post processing methods and accurate data reduction as well as simulations of slicer based integral field spectrographs. Experimental tests using a slicer and a preoptics setup designed to simulate the limiting noise are described in Chapter 6. Chapter 7 looks at using SINFONI for high contrast observations and Chapter 8 details the conclusions drawn from the work presented in this thesis, as well as possible extensions to it. The work performed in this thesis dispels the concerns about the continued one dimensional coherence up to the detecter and suggests that slicer based integral field spectrographs do not inherently limit the contrast achievable; Results from experiments fit well with the requirements for EPICS to achieve its goals. Simulations also supported the idea that secondary speckle noise should not be an issue for the slicer based IFS. This means that a slicer based IFS is a viable option for the EPICS instrument.

This semestral thesis deals with visualization of intracranial EEG. In the first part, theoretical basics of EEG is mentioned. After that, image registration, as a needed tool for visualization is described followed by research of methods of visualization of high frequency oscilations from intracranial EEG. Finally, method for visualization of high frequency oscilations from EEG in real MRI patient scans is designed and implemented.

In the past twenty years, the combination of the advances in medical imaging technologies and therapeutic methods had a great impact in developing minimally invasive interventional procedures. Although the use of medical imaging for the surgery and therapy guidance dates back to the early days of x-ray discovery, there is an increasing evidence in using the new imaging modalities such as computed tomography (CT), magnetic reso- nance imaging (MRI) and ultrasound in the operating rooms. The focus of this thesis is on developing image-guided interventional methods and techniques to support the radiation therapy treatment of gynecologic cancers. Gynecologic cancers which involves malignan- cies of the uterus, cervix, vagina and the ovaries are one of the top causes of mortality and morbidity among the women in U.S. and worldwide. The common treatment plan for radiation therapy of gynecologic cancers is chemotherapy and external beam radiation therapy followed by brachytherapy. Gynecological brachytherapy involves placement of interstitial catheters in and around the tumor area, often with the aid of an applicator. The goal is to create an optimal brachytherapy treatment plan that leads to maximal radiation dose to the cancerous tissue and minimal destructive radiation to the organs at risk. The accuracy of the catheter placement has a leading effect in the success of the treatment. However there are several techniques are developed for navigation of catheters and needles for procedures such as prostate biopsy, brain biopsy, and cardiac ablation, it is obviously lacking for gynecologic brachytherapy procedures. This thesis proposes a technique which aims to increase the accuracy and efficiency of catheter placements in gynecologic brachytherapy by guiding the catheters with an electromagnetic tracking system. To increase the accuracy of needle placement a navigation system has been set up and the appropriate software tools were developed and released for the public use as a module in the open-source 3D Slicer software. The developed technology can be translated from benchmark to the bedside to offer the potential benefit of maximizing tumor coverage during catheter placement while avoiding damage to the adjacent organs including bladder, rectum and bowel. To test the designed system two independent experiments were designed and performed on a phantom model in order to evaluate the targeting accuracy of the tracking system and the mean targeting error over all experiments was less than 2.9 mm, which can be compared to the targeting errors in the available commercial clinical navigation systems.

Dysphagia is a serious eating disorder currently affecting around 100 thousand people in Sweden and it’s estimated that 1 in 10 people will develop some form of dysphagia during their lifetime around the world. The condition occurs mainly in elders and people who’ve suffered a stroke. The disorder prohibits proper swallowing of food, impairing the ability to close airways and let food enter the proper pathways. Patients with dysphagia have to eat grounded food in order to not suffer from malnutrition. The food is usually served in timbales which are sometimes decorated but might not look as appealing or realistic as one might think. The repetitive and unrealistic food creates further appetite loss which may lead to malnutrition. This is the case amongst many elderly in home care and the complications maybe very serious indeed, leading to organ dysfunction, hospitalization and eventually death. The current timbales made at the kitchens for elderly care in Helsingborg are punched with a tool in rectangular, circular shapes and often decorated. A solution would be to increase the aesthetics of the served timbales and make them realistically looking. 3D printing offers numerous new opportunities for food production and may very well set a standard in the future for producing aesthetically pleasing food. Silicone molds may also provide the same, if not better results at the time being at a fraction of the price, sufficing to revert any negative impacts of the current timbale appearance. In the hopes of proving both concepts the work will initially be focused on preparing a broccoli but also applying one of the concepts on a cinnamon bun providing additional application. This report presents the progress of designing a realistic 3D broccoli model, product development of a realistic broccoli food mold, 3D scanning, 3D food printing and a literature study. The designed model could not be printed due to the printing gel’s incapability of supporting complex structures. Instead master shapes created for shaping the food mold were scanned, sliced and printed. The same masters were used as means for a second food mold. Both food molds did manage to cast realistic shapes with a broccoli puré and of a soft gelatine suspension. Material alternatives were evaluated as well as manufacturing possibilities. The designed broccoli and a refined scanned broccoli were both offered for free as means for further research and development.

This work explores machine learning as a tool for medical images' classification. A literary research is contained concerning both classical and modern approaches to image segmentation. The main purpose of this work is to design and implement an extension for the 3D Slicer platform. The extension uses machine learning to classify images using set parameters. The extension is tested on tomographic images obtained by nuclear magnetic resonance and observes the accuracy of the classification and usability in practice.

Indiana University-Purdue University Indianapolis (IUPUI) / With the recent advancement of computation and imaging technology, Image-based computational fluid dynamics (ICFD) has emerged as a great non-invasive capability to study biomedical flows. These modern technologies increase the potential of computation-aided diagnostics and therapeutics in a patient-specific environment. I studied three components of this image-based computational fluid dynamics process in this work. To ensure accurate medical assessment, realistic computational analysis is needed, for which patient-specific image segmentation of the diseased vessel is of paramount importance. In this work, image segmentation of several human arteries, veins, capillaries, and organs was conducted to use them for further hemodynamic simulations. To accomplish these, several open-source and commercial software packages were implemented. This study incorporates a new computational platform, called InVascular, to quantify the 4D velocity field in image-based pulsatile flows using the Volumetric Lattice Boltzmann Method (VLBM). We also conducted several parametric studies on an idealized case of a 3-D pipe with the dimensions of a human renal artery. We investigated the relationship between stenosis severity and Resistive index (RI). We also explored how pulsatile parameters like heart rate or pulsatile pressure gradient affect RI. As the process of ICFD analysis is based on imaging and other hemodynamic data, it is often time-consuming due to the extensive data processing time. For clinicians to make fast medical decisions regarding their patients, we need rapid and accurate ICFD results. To achieve that, we also developed surrogate models to show the potential of supervised machine learning methods in constructing efficient and precise surrogate models for Hagen-Poiseuille and Womersley flows.

<p>  </p> <p>With the recent advancement of computation and imaging technology, Image-based computational fluid dynamics (ICFD) has emerged as a great non-invasive capability to study biomedical flows. These modern technologies increase the potential of computation-aided diagnostics and therapeutics in a patient-specific environment. I studied three components of this image-based computational fluid dynamics process in this work.</p> <p>To ensure accurate medical assessment, realistic computational analysis is needed, for which patient-specific image segmentation of the diseased vessel is of paramount importance. In this work, image segmentation of several human arteries, veins, capillaries, and organs was conducted to use them for further hemodynamic simulations. To accomplish these, several open-source and commercial software packages were implemented. </p> <p>This study incorporates a new computational platform, called <em>InVascular</em>, to quantify the 4D velocity field in image-based pulsatile flows using the Volumetric Lattice Boltzmann Method (VLBM). We also conducted several parametric studies on an idealized case of a 3-D pipe with the dimensions of a human renal artery. We investigated the relationship between stenosis severity and Resistive index (RI). We also explored how pulsatile parameters like heart rate or pulsatile pressure gradient affect RI.</p> <p>As the process of ICFD analysis is based on imaging and other hemodynamic data, it is often time-consuming due to the extensive data processing time. For clinicians to make fast medical decisions regarding their patients, we need rapid and accurate ICFD results. To achieve that, we also developed surrogate models to show the potential of supervised machine learning methods in constructing efficient and precise surrogate models for Hagen-Poiseuille and Womersley flows.</p>