Physicians often utilize different imaging techniques to provide clear, visual information about internal parts of the patient. Since the different imaging modalities give different types of information, the combination of them serves as a powerful tool while determining the diagnosis, planning of treatment or during therapy follow-up. To simplify the interpretation of the image information, image registration is often used. The goal of the registration is to put different images in a common coordinate system. It is essential that the registration between the images is accurate. Normalized Mutual Information (NMI) is a metric that quantifies the conformity between images. Even though NMI is a robust method it is often dominated by large structures as the external contour of the patient as well as by the structures of the bones. The prostate is an organ that does not have a fixed position relative to the other organs and host small amounts of image information. The accuracy of the registration is therefore limited with respect to the prostate when using the whole image volume. This master thesis investigates the possibility to restrict the part of the image used for registration to a small volume around the prostate with goal to receive a better registration of the prostate than if full sized images are used. A registration program, utilizing NMI, was written and optimized in MatLab. Four Magnetic Resonance (MR) series and one Computed Tomographic (CT) series where taken over the pelvic area of five patients with the diagnosis prostate cancer. The prostate were delineated by a physician. By adding margin to the delineations five different sized Regions of Interest (ROI) where created.  The smallest ROI precisely covered the prostate while the largest covered the whole image. The deviation in Center of Mass (CoM) between the images and the Percentage Volume Overlap (PVO) were calculated and used as a measure of alignment. The registrations performed with sub-volumes showed an improvement compared to those that used full-volume while registering a MR image to another MR image. In one third of the cases a 2 cm margin to the prostate is preferable. A 3 cm margin is the most favorable option in another third of the cases. The use of sub-volumes to register MR images to CT series turned out to be unpredictable with poor accuracy. Full sized image registration between two MR image pairs has a high precision but, due to the motion of the prostate, poor accuracy. As a result of the high information content in the MR images both high precision as well as high accuracy can be achieved by the use of sub-volume registration. CT images do not contain the same amount of image information around the prostate and the sub-volume based registrations between MR and CT images are hence inconsistent with a low precision.  

The main objective of this thesis is the automatic modeling, understanding and segmentation of diffusively infiltrative tumors known as Diffuse Low-Grade Gliomas. Two approaches exploiting anatomical and spatial prior knowledge have been proposed. We first present the construction of a tumor specific probabilistic atlas describing the tumors' preferential locations in the brain. The proposed atlas constitutes an excellent tool for the study of the mechanisms behind the genesis of the tumors and provides strong spatial cues on where they are expected to appear. The latter characteristic is exploited in a Markov Random Field based segmentation method where the atlas guides the segmentation process as well as characterizes the tumor's preferential location. Second, we introduce a concurrent tumor segmentation and registration with missing correspondences method. The anatomical knowledge introduced by the registration process increases the segmentation quality, while progressively acknowledging the presence of the tumor ensures that the registration is not violated by the missing correspondences without the introduction of a bias. The method is designed as a hierarchical grid-based Markov Random Field model where the segmentation and registration parameters are estimated simultaneously on the grid's control point. The last contribution of this thesis is an uncertainty-driven adaptive sampling approach for such grid-based models in order to ensure precision and accuracy while maintaining robustness and computational efficiency. The potentials of both methods have been demonstrated on a large data-set of heterogeneous Diffuse Low-Grade Gliomas. The proposed methods go beyond the scope of the presented clinical context due to their strong modularity and could easily be adapted to other clinical or computer vision problems.

Prostate cancer is a worldwide health concern for men. Needle biopsy is the most definitive form of cancer diagnosis. Target-specific biopsies can be performed under magnetic resonance imaging (MRI) guidance. However, needle placements are often inaccurate due to intra-operative prostate motion and the lack of motion compensation techniques. As a result, malignant tumors can be missed, which in turn will lead to an increased number of repeated biopsies and delaying of treatment. To increase the needle targeting accuracy, intra-operative prostate motion and deformation need to be studied so that motion compensation techniques can be developed accordingly. This thesis intends to make three main contributions: 1. A comprehensive survey of the state-of-art in image-guided prostate needle placement interventions. 2. Retrospective clinical accuracy validation of a MRI-guided robotic prostate biopsy system that was used in the U.S. National Cancer Institute for over 6 years. A 3D-3D registration algorithm consists of an initial two-step rigid alignment followed by a B-spline deformable transform was developed to align the pre- and post-needle insertion images. A total of 90 biopsies from 24 patients were studied. The mean target displacement, needle placement error, and clinical biopsy error were 5.2, 2.5, and 4.3 mm, respectively. 3. Development of a multi-slice-to-volume registration for intra-operative target localization. The algorithm aligns the planning volume with three orthogonal image slices of the prostate acquired immediately before needle insertion. It consists of a rigid registration followed by a deformable step using only the prostate region. The algorithm was validated on 14 clinical images sets from Brigham and Women's Hospital in Boston, Massachusetts. All registration errors were well below the radius of a clinically significant tumour (5 mm), and are considered clinically acceptable. The results show that there was a substantial amount of biopsy error caused by prostate motion and deformation during MRI-guided biopsy. This error can be reduced by using quantitative imaging techniques for prostate registration and motion compensation. In particular, the multi-slice-to-volume registration algorithm demonstrated the feasibility of intra-operative target localization and motion compensation; which in turn may improve the quality of MRI-guided prostate interventions. / Thesis (Ph.D, Computing) -- Queen's University, 2014-03-01 11:45:55.8

An interesting problem in computer vision is that of image registration, which plays an important role in many vision-based recognition and motion analysis applications. Of particular interest among data registration problems are multimodal image registration problems, where the image data sets are acquired using different imaging modalities. There are several important issues that make real-world multimodal registration a difficult problem to solve. First, images are often characterized by illumination and contrast non-uniformities. Such image non-uniformities result in local minima along the convergence plane that make it difficult for local optimization schemes to converge to the correct solution. Second, real-world images are often contaminated with signal noise, making the extraction of meaningful features for comparison purposes difficult to accomplish. Third, feature space differences make performing direct comparisons between the different data sets with a reasonable level of accuracy a challenging problem. Finally, solving the multimodal registration problem can be computationally expensive for large images. This thesis presents a probabilistic complex phase representation (PCPR) objective function for registering images acquired using different imaging modalities. A probabilistic multi-scale approach is introduced to create image representations based on local phase relationships extracted using complex wavelets. An objective function is introduced for assessing the alignment between the images based on a Geman-McClure error distribution model between the probabilistic complex phase representations of the images. Experimental results show that the proposed PCPR objective function can provide improved registration accuracies when compared to existing objective functions.

Modern image-guided surgery aids minimally-invasive, high-precision procedures that increase efficacy of treatment. This thesis investigates two research aims to improve precision and integration of intraoperative cone-beam CT (CBCT) imaging in guidance of head and neck (H&N) surgery. First, marker configurations were examined to identify arrangements that minimize target registration error (TRE). Best arrangements minimized the distance between the configuration centroid and surgical target while maximizing marker separation. Configurations of few markers could minimized TRE with more markers providing improved uniformity. Second, an algorithm for automatic registration of image and world reference frames was pursued to streamline integration of CBCT with real-time tracking and provide automatic updates per scan. Markers visible to the tracking and imaging systems are automatically co-localized and registered with equivalent accuracy and superior reproducibility compared to conventional registration. Such work helps the implementation of CBCT in H&N surgery to maximize surgical precision and exploit intraoperative image guidance.

Modern image-guided surgery aids minimally-invasive, high-precision procedures that increase efficacy of treatment. This thesis investigates two research aims to improve precision and integration of intraoperative cone-beam CT (CBCT) imaging in guidance of head and neck (H&N) surgery. First, marker configurations were examined to identify arrangements that minimize target registration error (TRE). Best arrangements minimized the distance between the configuration centroid and surgical target while maximizing marker separation. Configurations of few markers could minimized TRE with more markers providing improved uniformity. Second, an algorithm for automatic registration of image and world reference frames was pursued to streamline integration of CBCT with real-time tracking and provide automatic updates per scan. Markers visible to the tracking and imaging systems are automatically co-localized and registered with equivalent accuracy and superior reproducibility compared to conventional registration. Such work helps the implementation of CBCT in H&N surgery to maximize surgical precision and exploit intraoperative image guidance.

Darbe tiriamos eismo įvykio schemos braižymo ir eismo įvykio deklaracijos užpildymo automatizavimo galimybės. Tirtos šios kryptys: • GPS ir elektroninių žemėlapių panaudojimas • Atstumo matuoklių panaudojimas • Lustinių kortelių skaitytuvų panaudojimas • Automatinis ataskaitų generavimas Sukurta eksperimentinė eismo įvykių registravimo sistema, skirta bandymų rezultatams pademonstruoti. / The subject of investigation of the work is the prospects and possibilities of automation in composing traffic accident declaration. The suggestions provided: • The employment of GPS and e-maps • Usage of distance measurement devices • Appliance of chip card readers • Automatic formation of reports An experimental traffic accident registration system, demonstrating the outcomes of the research was created.

ITIL tai eilė dokumentų, kurie naudojami siekiant padėti įdiegti IT paslaugų valdymo struktūrą. Ši individualiai pagal įmonės poreikius pritaikoma struktūra nustato, kaip paslaugų valdymas vykdomas konkrečioje įmonėje arba verslo teorija, orientuota į darbo optimizavimą bei kokybės užtikrinimą IT kompanijose. Mūsų darbo tyrimo sritis buvo modifikuoto incidentų eskalavimo algoritmas, jo modifikacija ir pritaikymas sistemoje. Bei rezultatų palyginimas su ITIL metodologija paremtu algoritmu. Tikslas – susisteminti IT ūkio sprendžiamas problemas. / The Information Technology Infrastructure Library is a framework of best practice approaches intended to facilitate the delivery of high quality information technology services. ITIL outlines an extensive set of management procedures that are intended to support businesses in achieving both high financial quality and value in IT operations. Our made-up computer technology and software failure system is based on ITIL methodology. We suggested modified incidents priority lifting algorithm, which presents better row of troubles.

Kubickas E., Kalbančiojo lūpų formos registravimas: Elektronikos inžinerijos magistro darbas/mokslinis vadovas doc. dr. G. Daunys; Šiaulių universitetas, Technologijos fakultetas, Elektronikos katedra, – Šiauliai, 2007. – 67p. Magistro darbo tema yra aktuali, kadangi lūpos yra vienas svarbiausių vizualinės kalbos dalių. Komunikuojant žmonėms svarbiausi informacijos kanalai yra kalbos ir vizualiniai ženklai. Norint suprasti vartotojo instrukcijas triukšmingoje aplinkoje kompiuteris turi pasikliauti vizualiniais vartotojo ženklais. Šiame darbe atliekamas lūpų formos registravimas pasitelkus OpenCV ir Matlab 7.0 paketą. Pagrindinis tikslas yra sudaryti ir išanalizuoti algoritmą tiksliam lūpų formos registravimui. Ištyrinėta 4 žmonių lūpų forma (kontūrai). Remiantis gautais rezultatais matyti, kad lūpų registravimas susijęs su keletu problemų – sudėtingas lūpų registravimas dėl panašios veido spalvos, taip pat sudėtingas vidinių kontūrų radimas dėl matomų artikuliatorių. Tiksliausiai lūpų forma registruojama naudojant žalios spalvos komponentę (G). Gauti rezultatai gali būti panaudoti tolesniems tyrinėjimams, tokiems kaip neuroninių tinklų apmokymas lūpų padėčiai ar raidėms atpažinti. / Kubickas E. Speaker lip shape registration: Master thesis of electronics engineer/research advisor Assoc. Dr. G. Daunys; Šiaulių University, Technological Faculty, Electronics Department. – Šiauliai, 2007. – 67 p. The theme of Master Project of Electronics engineer is actual, because the lip is the one of the principal visual speech part. For better users instruction‘s understanding in the noisy environment, computer must rely on the visual users signs. In the theory section there is described the most important channels for communication - speech and visual signs. There is performing lip shape registration by using OpenCv and Matlab 7.0 package in this work. The approach proposed to make and to analize algorithm for more accurate lip registration. The main task is to investigate how to detect speaker lip shape robustly, when their location is different. There is presented research of four people lip‘s shape (contours). The results showed that there are few problems, related with lip registration – difficult lip extraction because of the similar skin colour, problematic lips inner contours extraction, because of the visible articulators such as teeth, tongue. Above all, that the main task was reached – there was received the robust lip registration by green colours component. Received results can be used for the further investigations such as different expression pictures research, the neural network for lip position or letters recognizing training.

Prostate cancer continues to be the most commonly diagnosed cancer among men. Brachytherapy has emerged as one of the definitive treatment options for early stage prostate cancer which entails permanent implantation of radioactive seeds into the prostate to eradicate the cancer with ionizing radiation. Successful brachytherapy requires the ability to perform dosimetry -which requires seed localization- during the procedure but such function is not available today. If dosimetry could be performed intraoperatively, physicians could implant additional seeds into the under-dosed portions of the prostate while the patient is still on the operating table. This thesis addresses the brachytherapy seed localization problem with introducing intensity based registration between transrectal ultrasound (TRUS) that shows only the prostate and a 3D seed model drawn from fluoroscopy that shows only the implanted seeds. The TRUS images are first filtered and compounded, and then registered to the seed model by using mutual information. A training phantom was implanted with 48 seeds and imaged. Various ultrasound filtering techniques were analyzed. The effect of false positives and false negatives in ultrasound was investigated by randomly masking seeds from the fluoroscopy volume or adding seeds to that in random locations. Furthermore, the effect of sparse and dense ultrasound data was analyzed by running the registration for ultrasound data with different spacing. The registration error remained consistently below clinical threshold and capture range was significantly larger than the initial guess guaranteed by the clinical workflow. This fully automated method provided excellent registration accuracy and robustness in phantom studies and promises to demonstrate clinically adequate performance on human data. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2008-09-27 12:35:16.691