Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multipinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target’s radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals.

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

Effect of image resolution manipulation in rearfoot angle measurements obtained with photogrammetry

The aim of this study was to investigate the influence of image resolution manipulation on the photogrammetric measurement of the rearfoot static angle. The study design was that of a reliability study. We evaluated 19 healthy young adults (11 females and 8 males). The photographs were taken at 1536 pixels in the greatest dimension, resized into four different resolutions (1200, 768, 600, 384 pixels) and analyzed by three equally trained examiners on a 96-pixels per inch (ppi) screen. An experienced physiotherapist marked the anatomic landmarks of rearfoot static angles on two occasions within a 1-week interval. Three different examiners had marked angles on digital pictures. The systematic error and the smallest detectable difference were calculated from the angle values between the image resolutions and times of evaluation. Different resolutions were compared by analysis of variance. Inter- and intra-examiner reliability was calculated by intra-class correlation coefficients (ICC). The rearfoot static angles obtained by the examiners in each resolution were not different (P > 0.05); however, the higher the image resolution the better the inter-examiner reliability. The intra-examiner reliability (within a 1-week interval) was considered to be unacceptable for all image resolutions (ICC range: 0.08-0.52). The whole body image of an adult with a minimum size of 768 pixels analyzed on a 96-ppi screen can provide very good inter-examiner reliability for photogrammetric measurements of rearfoot static angles (ICC range: 0.85-0.92), although the intra-examiner reliability within each resolution was not acceptable. Therefore, this method is not a proper tool for follow-up evaluations of patients within a therapeutic protocol.

Striatal and extrastriatal dopamine D2/3 receptors studied with [11C]raclopride and high-resolution PET

The human striatum is a heterogeneous structure representing a major part of the dopamine (DA) system’s basal ganglia input and output. Positron emission tomography (PET) is a powerful tool for imaging DA neurotransmission. However, PET measurements suffer from bias caused by the low spatial resolution, especially when imaging small, D2/3 -rich structures such as the ventral striatum (VST). The brain dedicated high-resolution PET scanner, ECAT HRRT (Siemens Medical Solutions, Knoxville, TN, USA) has superior resolution capabilities than its predecessors. In the quantification of striatal D2/3 binding, the in vivo highly selective D2/3 antagonist [11C] raclopride is recognized as a well-validated tracer. The aim of this thesis was to use a traditional test-retest setting to evaluate the feasibility of utilizing the HRRT scanner for exploring not only small brain regions such as the VST but also low density D2/3 areas such as cortex. It was demonstrated that the measurement of striatal D2/3 binding was very reliable, even when studying small brain structures or prolonging the scanning interval. Furthermore, the cortical test-retest parameters displayed good to moderate reproducibility. For the first time in vivo, it was revealed that there are significant divergent rostrocaudal gradients of [11C]raclopride binding in striatal subregions. These results indicate that high-resolution [11C]raclopride PET is very reliable and its improved sensitivity means that it should be possible to detect the often very subtle changes occurring in DA transmission. Another major advantage is the possibility to measure simultaneously striatal and cortical areas. The divergent gradients of D2/3 binding may have functional significance and the average distribution binding could serve as the basis for a future database. Key words: dopamine, PET, HRRT, [11C]raclopride, striatum, VST, gradients, test-retest.

Developing correlative Optical-Photoacustic microscopy for high-resolution in vivo imaging

PhotoAcoustic Imaging (PAI) is a branch in clinical and pre-clinical imaging, that refers to the techniques mapping acoustic signals caused by the absorption of the short laser pulse. This conversion of electromagnetic energy of the light to the mechanical (acoustic) energy is usually called photoacoustic effect. PAI, by combining optical excitation with acoustical detection, is able to preserve the diffraction limited spatial resolution. At the same time, the penetration depth is extended beyond the diffusive limit. The Laser-Scanning PhotoAcoustic Microscope system (LS-PAM) has been developed, that offers the axial resolution of 7.75 µm with the lateral resolution better than 10 µm. The first in vivo imaging experiments were carried out. Thus, in vivo label-free imaging of the mouse ear was performed. The principle possibility to image vessels located in deep layers of the mouse skin was shown. As well as that, a gold printing sample, vasculature of the Chick Chorioallantoic Membrane Assay, Drosophila larvae were imaged by PAI. During the experimental work, a totally new application of PAM was found, in which the acoustic waves, generated by incident light can be used for further imaging of another sample. In order to enhance the performance of the presented system two main recommendation can be offered. First, the current system should be transformed into reflection-mode setup system. Second, a more powerful source of light with the sufficient repetition rate should be introduced into the system.

Development of 3D super-resolution tomographic STED microscopy and its application to studies on bone resorption

In this doctoral thesis, a tomographic STED microscopy technique for 3D super-resolution imaging was developed and utilized to observebone remodeling processes. To improve upon existing methods, wehave used a tomographic approach using a commercially available stimulated emission depletion (STED) microscope. A certain region of interest (ROI) was observed at two oblique angles: one at a standard inverted configuration from below (bottom view) and another from the side (side view) via a micro-mirror positioned close to the ROI. The two viewing angles were reconstructed into a final tomogram. The technique, named as tomographic STED microscopy, was able to achieve an axial resolution of approximately 70 nm on microtubule structures in a fixed biological specimen. High resolution imaging of osteoclasts (OCs) that are actively resorbing bone was achieved by creating an optically transparent coating on a microscope coverglass that imitates a fractured bone surface. 2D super-resolution STED microscopy on the bone layer showed approximately 60 nm of lateral resolution on a resorption associated organelle allowing these structures to be imaged with super-resolution microscopy for the first time. The developed tomographic STED microscopy technique was further applied to study resorption mechanisms of OCs cultured on the bone coating. The technique revealed actin cytoskeleton with specific structures, comet-tails, some of which were facing upwards and some others were facing downwards. This, in our opinion, indicated that during bone resorption, an involvement of the actin cytoskeleton in vesicular exocytosis and endocytosis is present. The application of tomographic STED microscopy in bone biology demonstrated that 3D super-resolution techniques can provide new insights into biological 3D nano-structures that are beyond the diffraction-limit when the optical constraints of super-resolution imaging are carefully taken into account.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Bioimage informatics in STED super-resolution microscopy

Optical microscopy is living its renaissance. The diffraction limit, although still physically true, plays a minor role in the achievable resolution in far-field fluorescence microscopy. Super-resolution techniques enable fluorescence microscopy at nearly molecular resolution. Modern (super-resolution) microscopy methods rely strongly on software. Software tools are needed all the way from data acquisition, data storage, image reconstruction, restoration and alignment, to quantitative image analysis and image visualization. These tools play a key role in all aspects of microscopy today – and their importance in the coming years is certainly going to increase, when microscopy little-by-little transitions from single cells into more complex and even living model systems. In this thesis, a series of bioimage informatics software tools are introduced for STED super-resolution microscopy. Tomographic reconstruction software, coupled with a novel image acquisition method STED< is shown to enable axial (3D) super-resolution imaging in a standard 2D-STED microscope. Software tools are introduced for STED super-resolution correlative imaging with transmission electron microscopes or atomic force microscopes. A novel method for automatically ranking image quality within microscope image datasets is introduced, and it is utilized to for example select the best images in a STED microscope image dataset.

Power and Performance Management Strategies on NoC-Based Multicore Platforms, Using DVFS, Adaptive Algorithm and Task Parallelism

This work presents synopsis of efficient strategies used in power managements for achieving the most economical power and energy consumption in multicore systems, FPGA and NoC Platforms. In this work, a practical approach was taken, in an effort to validate the significance of the proposed Adaptive Power Management Algorithm (APMA), proposed for system developed, for this thesis project. This system comprise arithmetic and logic unit, up and down counters, adder, state machine and multiplexer. The essence of carrying this project firstly, is to develop a system that will be used for this power management project. Secondly, to perform area and power synopsis of the system on these various scalable technology platforms, UMC 90nm nanotechnology 1.2v, UMC 90nm nanotechnology 1.32v and UMC 0.18 μmNanotechnology 1.80v, in order to examine the difference in area and power consumption of the system on the platforms. Thirdly, to explore various strategies that can be used to reducing system’s power consumption and to propose an adaptive power management algorithm that can be used to reduce the power consumption of the system. The strategies introduced in this work comprise Dynamic Voltage Frequency Scaling (DVFS) and task parallelism. After the system development, it was run on FPGA board, basically NoC Platforms and on these various technology platforms UMC 90nm nanotechnology1.2v, UMC 90nm nanotechnology 1.32v and UMC180 nm nanotechnology 1.80v, the system synthesis was successfully accomplished, the simulated result analysis shows that the system meets all functional requirements, the power consumption and the area utilization were recorded and analyzed in chapter 7 of this work. This work extensively reviewed various strategies for managing power consumption which were quantitative research works by many researchers and companies, it's a mixture of study analysis and experimented lab works, it condensed and presents the whole basic concepts of power management strategy from quality technical papers.

Real-time monitoring of laser scribing process utilizing high-speed camera

Currently, laser scribing is growing material processing method in the industry. Benefits of laser scribing technology are studied for example for improving an efficiency of solar cells. Due high-quality requirement of the fast scribing process, it is important to monitor the process in real time for detecting possible defects during the process. However, there is a lack of studies of laser scribing real time monitoring. Commonly used monitoring methods developed for other laser processes such a laser welding, are sufficient slow and existed applications cannot be implemented in fast laser scribing monitoring. The aim of this thesis is to find a method for laser scribing monitoring with a high-speed camera and evaluate reliability and performance of the developed monitoring system with experiments. The laser used in experiments is an IPG ytterbium pulsed fiber laser with 20 W maximum average power and Scan head optics used in the laser is Scanlab’s Hurryscan 14 II with an f100 tele-centric lens. The camera was connected to laser scanner using camera adapter to follow the laser process. A powerful fully programmable industrial computer was chosen for executing image processing and analysis. Algorithms for defect analysis, which are based on particle analysis, were developed using LabVIEW system design software. The performance of the algorithms was analyzed by analyzing a non-moving image from the scribing line with resolution 960x20 pixel. As a result, the maximum analysis speed was 560 frames per second. Reliability of the algorithm was evaluated by imaging scribing path with a variable number of defects 2000 mm/s when the laser was turned off and image analysis speed was 430 frames per second. The experiment was successful and as a result, the algorithms detected all defects from the scribing path. The final monitoring experiment was performed during a laser process. However, it was challenging to get active laser illumination work with the laser scanner due physical dimensions of the laser lens and the scanner. For reliable error detection, the illumination system is needed to be replaced.

Detection of Epilepsy with a Commercial EEG Headband

Epilepsy is a chronic brain disorder, characterized by reoccurring seizures. Automatic sei-zure detector, incorporated into a mobile closed-loop system, can improve the quality of life for the people with epilepsy. Commercial EEG headbands, such as Emotiv Epoc, have a potential to be used as the data acquisition devices for such a system. In order to estimate that potential, epileptic EEG signals from the commercial devices were emulated in this work based on the EEG data from a clinical dataset. The emulated characteristics include the referencing scheme, the set of electrodes used, the sampling rate, the sample resolution and the noise level. Performance of the existing algorithm for detection of epileptic seizures, developed in the context of clinical data, has been evaluated on the emulated commercial data. The results show, that after the transformation of the data towards the characteristics of Emotiv Epoc, the detection capabilities of the algorithm are mostly preserved. The ranges of acceptable changes in the signal parameters are also estimated.

GIS-based approach for optimization of onshore wind park infrastructure alignment in Finland

Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.

Using classroom meetings to transfer conflict resolution skills /

This study examined whether daily classroom meetings resulted in the positive transfer of conflict resolution information and skills beyond the formal classroom setting and into the classroom. A control group of sixteen Grade five students received three weeks of conflict resolution training and an experimental group of nineteen Grade five students fi-om the same school received three weeks of conflict resolution training followed by three additional weeks of class meetings. Pretest measures were taken via a scaled questionnaire and short answer questions before the conflict resolution lessons began for the following skills: knowledge of conflict resolution; conflict resolution behaviour; and attitude about using conflict resolution to resolve problems with other people. Posttest measures examined conflict resolution skills following involvement in the study. Students chosen randomly and both teachers were interviewed following the study. The teachers were again interviewed three months after the study. Teacher journal notes rounded out the data. The results of the study indicated that the Grade five boys who participated in three weeks of conflict resolution training did not increase their conflict resolution skills in any of the areas examined. Girls who participated in three weeks of conflict resolution training did not improve in two areas (i.e., behaviour, knowledge) and became less positive about using verbal mediation to resolve conflicts. The Grade five students who participated in three weeks of training and three weeks of class meetings obtained different results. The boys improved significantly in their ability to use verbal mediation to resolve conflicts and were more positive about verbal mediation. They did not become more knowledgeable about verbal mediation. The girls who participated in three weeks of training and three weeks of class meetings were more knowledgeable of conflict resolution and used conflict resolution to solve problems with other people. However, they were significantly less positive about using these skills to resolve problems.

Confocal and two-photon microscopy : image enhancement /

Confocal and two-photon microcopy have become essential tools in biological research and today many investigations are not possible without their help. The valuable advantage that these two techniques offer is the ability of optical sectioning. Optical sectioning makes it possible to obtain 3D visuahzation of the structiu-es, and hence, valuable information of the structural relationships, the geometrical, and the morphological aspects of the specimen. The achievable lateral and axial resolutions by confocal and two-photon microscopy, similar to other optical imaging systems, are both defined by the diffraction theorem. Any aberration and imperfection present during the imaging results in broadening of the calculated theoretical resolution, blurring, geometrical distortions in the acquired images that interfere with the analysis of the structures, and lower the collected fluorescence from the specimen. The aberrations may have different causes and they can be classified by their sources such as specimen-induced aberrations, optics-induced aberrations, illumination aberrations, and misalignment aberrations. This thesis presents an investigation and study of image enhancement. The goal of this thesis was approached in two different directions. Initially, we investigated the sources of the imperfections. We propose methods to eliminate or minimize aberrations introduced during the image acquisition by optimizing the acquisition conditions. The impact on the resolution as a result of using a coverslip the thickness of which is mismatched with the one that the objective lens is designed for was shown and a novel technique was introduced in order to define the proper value on the correction collar of the lens. The amoimt of spherical aberration with regard to t he numerical aperture of the objective lens was investigated and it was shown that, based on the purpose of our imaging tasks, different numerical apertures must be used. The deformed beam cross section of the single-photon excitation source was corrected and the enhancement of the resolution and image quaUty was shown. Furthermore, the dependency of the scattered light on the excitation wavelength was shown empirically. In the second part, we continued the study of the image enhancement process by deconvolution techniques. Although deconvolution algorithms are used widely to improve the quality of the images, how well a deconvolution algorithm responds highly depends on the point spread function (PSF) of the imaging system applied to the algorithm and the level of its accuracy. We investigated approaches that can be done in order to obtain more precise PSF. Novel methods to improve the pattern of the PSF and reduce the noise are proposed. Furthermore, multiple soiu'ces to extract the PSFs of the imaging system are introduced and the empirical deconvolution results by using each of these PSFs are compared together. The results confirm that a greater improvement attained by applying the in situ PSF during the deconvolution process.