Abstract Medical x-ray imaging is used to visualise patients’ anatomical structures and in some cases their physiology. X-rays are ionizing radiation, thus their use needs to be optimised, as stochastic effects are assumed to increase linearly with the exposure dose. Imaging protocols need to be optimised to a radiation dose level that follows the as low as reasonably achievable principle without compromising the diagnostic value of the image. Different methods can be used to help in the optimisation process, such as simulations, radiation dose and image quality assessments with dosimeters and phantoms and utilising the latest technology in the most efficient way. The purpose of this doctoral thesis was to investigate the applicability of metal-oxide-semiconductor-field-effect-transistor (MOSFET) dosimeters for dose determinations in conventional x-ray and computed tomography (CT) examinations. Additionally, dose optimising methods were investigated in dental panoramic imaging using radiophotoluminescence (RPL) dosimeters. Anthropomorphic phantoms were used in every study to simulate patients, as their structures enable dosimeters to be positioned at locations that correspond to different organs. The MOSFET’s properties for dose determinations were evaluated against the reference dosimeter in a conventional x-ray set-up. Comparisons of absorbed and effective doses in thorax x-ray imaging were made between RPLs, MOSEFTs and Monte Carlo simulations. The effect of the organ-based tube current modulation and bismuth shields were compared against the reference imaging method in a chest CT with one scanner model. Absorbed doses and quantitative image quality were evaluated using each method. Possible dose reduction from segmented dental panoramic tomography (sDPT) imaging was compared against full DPT. Dose measurements were done using RPL dosimeters in pediatric and adult set-up using phantoms. MOSFETs are accurate enough to be used in conventional x-ray and CT, but they require a careful calibration before use as their reproducibility is limited with low doses. Bismuth shields provided the best dose reduction, but with a negative impact on quantitative image quality, especially when metal artefact removal software was used. The final study showed that the use of sDPT programmes and pediatric protocols enable a notably dose reduction compared to the full DPT adult protocol. / Tiivistelmä Lääketieteellisessä kuvantamisessa käytetään röntgensäteilyä potilaan anatomian ja joissain tapauksissa fysiologian visualisointiin. Röntgensäteily on ionisoivaa ja stokastisten vaikutusten kasvaessa oletettavasti lineaarisesti säteilyn funktiona, tulee säteilyn olla kokonaisvaltaisesti optimoitua. Kuvauksissa käytetyn röntgensäteilyn käytön tulee noudattaa ALARA-periaatetta, minkä vuoksi kuvauksessa tulee käyttää niin vähän säteilyä kuin vain mahdollista, diagnostiikan vaarantumatta. Optimoinnin apuna voidaan käyttää esim. simulointeja, annos- ja kuvanlaatumäärityksiä dosimetreilla ja fantomeilla, tai laitevalmistajien tuomia uusia teknologioita. Tämän väitöskirjan tarkoituksena oli tutkia metallioksidi-puolijohdekanavatransistorien (MOSFET) soveltuvuutta natiiviröntgentutkimuksissa ja tietokonetomografiassa (TT). Lisäksi työssä tutkittiin hammaskuvauksissa käytettyjä annossäästömenetelmiä radiofotoluminesenssidosimetreilla (RPL). Potilasvasteena työssä käytettiin antropomorfisia fantomeita, minkä ansiosta säteilyannoksia voidaan mitata eri elimiä vastaavilta kohdilta. MOSFET annosmittarin ominaisuuksia arvioitiin natiiviröntgenasetelmassa referenssimittariin nähden. Absorboituneiden ja efektiivisten annosten eroa MOSFET:tien, RPL:ien ja simulointien kesken tutkittiin keuhkoröntgentutkimuksessa. Pintakudoksia säästävän putkivirranmodulointimenetelmän ja vismuttisuojien vaikuttavuutta verrattiin TT:ssä referenssimetelmää vasten. Vaikuttavuutta arvioitiin absorboituneiden annosten ja kvantitatiivisen kuvanlaadun avulla. Segmentoidun hammaspanoraamakuvauksen (sDPT) annossäästömahdollisuuksia verrattiin tavalliseen panoraamakuvaukseen. Annosmääritykset tehtiin käyttäen RPL dosimetreja lapsi- ja aikuisfantomeissa. MOSFET dosimetreja voidaan käyttää annosmäärityksiin natiiviröntgenkuvauksissa ja TT:ssä, mutta niiden kalibrointi ja toistettavuus matalilla annoksilla aiheuttaa kuitenkin rajoituksia niiden käytölle. Vismuttisuojat tuottivat parhaan annossäästön, huonontaen kuitenkin kuvanlaatua. Kuvanlaadun huonontuminen oli erityisen huomattavaa, kun metallista aiheutuvien kuvavirheiden poistamiseen suunniteltua ohjelmaa käytettiin. Viimeinen tutkimus osoitti, että sDPT ohjelmat ja lapsille suunnatut protokollat mahdollistavat huomattavan annossäästön verrattuna aikuisten kokopanoraamaan.

The topic of this thesis is design of a panoramic X-ray. The main contribution is a new view on ergonomics of operator and a possibility of seating for patient. The aim is to create a device with innovative seating incorporated into the supporting leg of the machine, and to improve an ergonomics of machine manipulation. But it is also necessary to maintain all the technical, ergonomic, aesthetic and environmental requirements. The final draft should be able compete with existing products on the market.

Real-world radiance values can range over eight orders of magnitude from starlight to direct sunlight but few digital cameras capture more than three orders in a single Low Dynamic Range (LDR) image. We approach this problem using established High Dynamic Range (HDR) techniques in which multiple images are captured with different exposure times so that all portions of the scene are correctly exposed at least once. These images are then combined to create an HDR image capturing the full range of the scene. HDR capture introduces new challenges; movement in the scene creates faded copies of moving objects, referred to as ghosts. Many techniques have been introduced to handle ghosting, but typically they either address specific types of ghosting, or are computationally very expensive. We address ghosting by first detecting moving objects, then reducing their contribution to the final composite on a frame-by-frame basis. The detection of motion is addressed by performing change detection on exposure-normalized images. Additional special cases are developed based on a priori knowledge of the changing exposures; for example, if exposure is increasing every shot, then any decrease in intensity in the LDR images is a strong indicator of motion. Recent Superpixel over-segmentation techniques are used to refine the detection. We also propose a novel solution for areas that see motion throughout the capture, such as foliage blowing in the wind. Such areas are detected as always moving, and are replaced with information from a single input image, and the replacement of corrupted regions can be tailored to the scenario. We present our approach in the context of a panoramic tele-presence system. Tele-presence systems allow a user to experience a remote environment, aiming to create a realistic sense of "being there" and such a system should therefore provide a high quality visual rendition of the environment. Furthermore, panoramas, by virtue of capturing a greater proportion of a real-world scene, are often exposed to a greater dynamic range than standard photographs. Both facets of this system therefore stand to benefit from HDR imaging techniques. We demonstrate the success of our approach on multiple challenging ghosting scenarios, and compare our results with state-of-the-art methods previously proposed. We also demonstrate computational savings over these methods.

Real-world radiance values can range over eight orders of magnitude from starlight to direct sunlight but few digital cameras capture more than three orders in a single Low Dynamic Range (LDR) image. We approach this problem using established High Dynamic Range (HDR) techniques in which multiple images are captured with different exposure times so that all portions of the scene are correctly exposed at least once. These images are then combined to create an HDR image capturing the full range of the scene. HDR capture introduces new challenges; movement in the scene creates faded copies of moving objects, referred to as ghosts. Many techniques have been introduced to handle ghosting, but typically they either address specific types of ghosting, or are computationally very expensive. We address ghosting by first detecting moving objects, then reducing their contribution to the final composite on a frame-by-frame basis. The detection of motion is addressed by performing change detection on exposure-normalized images. Additional special cases are developed based on a priori knowledge of the changing exposures; for example, if exposure is increasing every shot, then any decrease in intensity in the LDR images is a strong indicator of motion. Recent Superpixel over-segmentation techniques are used to refine the detection. We also propose a novel solution for areas that see motion throughout the capture, such as foliage blowing in the wind. Such areas are detected as always moving, and are replaced with information from a single input image, and the replacement of corrupted regions can be tailored to the scenario. We present our approach in the context of a panoramic tele-presence system. Tele-presence systems allow a user to experience a remote environment, aiming to create a realistic sense of "being there" and such a system should therefore provide a high quality visual rendition of the environment. Furthermore, panoramas, by virtue of capturing a greater proportion of a real-world scene, are often exposed to a greater dynamic range than standard photographs. Both facets of this system therefore stand to benefit from HDR imaging techniques. We demonstrate the success of our approach on multiple challenging ghosting scenarios, and compare our results with state-of-the-art methods previously proposed. We also demonstrate computational savings over these methods.

No description available.

Real-world radiance values can range over eight orders of magnitude from starlight to direct sunlight but few digital cameras capture more than three orders in a single Low Dynamic Range (LDR) image. We approach this problem using established High Dynamic Range (HDR) techniques in which multiple images are captured with different exposure times so that all portions of the scene are correctly exposed at least once. These images are then combined to create an HDR image capturing the full range of the scene. HDR capture introduces new challenges; movement in the scene creates faded copies of moving objects, referred to as ghosts. Many techniques have been introduced to handle ghosting, but typically they either address specific types of ghosting, or are computationally very expensive. We address ghosting by first detecting moving objects, then reducing their contribution to the final composite on a frame-by-frame basis. The detection of motion is addressed by performing change detection on exposure-normalized images. Additional special cases are developed based on a priori knowledge of the changing exposures; for example, if exposure is increasing every shot, then any decrease in intensity in the LDR images is a strong indicator of motion. Recent Superpixel over-segmentation techniques are used to refine the detection. We also propose a novel solution for areas that see motion throughout the capture, such as foliage blowing in the wind. Such areas are detected as always moving, and are replaced with information from a single input image, and the replacement of corrupted regions can be tailored to the scenario. We present our approach in the context of a panoramic tele-presence system. Tele-presence systems allow a user to experience a remote environment, aiming to create a realistic sense of "being there" and such a system should therefore provide a high quality visual rendition of the environment. Furthermore, panoramas, by virtue of capturing a greater proportion of a real-world scene, are often exposed to a greater dynamic range than standard photographs. Both facets of this system therefore stand to benefit from HDR imaging techniques. We demonstrate the success of our approach on multiple challenging ghosting scenarios, and compare our results with state-of-the-art methods previously proposed. We also demonstrate computational savings over these methods.

Real-world radiance values can range over eight orders of magnitude from starlight to direct sunlight but few digital cameras capture more than three orders in a single Low Dynamic Range (LDR) image. We approach this problem using established High Dynamic Range (HDR) techniques in which multiple images are captured with different exposure times so that all portions of the scene are correctly exposed at least once. These images are then combined to create an HDR image capturing the full range of the scene. HDR capture introduces new challenges; movement in the scene creates faded copies of moving objects, referred to as ghosts. Many techniques have been introduced to handle ghosting, but typically they either address specific types of ghosting, or are computationally very expensive. We address ghosting by first detecting moving objects, then reducing their contribution to the final composite on a frame-by-frame basis. The detection of motion is addressed by performing change detection on exposure-normalized images. Additional special cases are developed based on a priori knowledge of the changing exposures; for example, if exposure is increasing every shot, then any decrease in intensity in the LDR images is a strong indicator of motion. Recent Superpixel over-segmentation techniques are used to refine the detection. We also propose a novel solution for areas that see motion throughout the capture, such as foliage blowing in the wind. Such areas are detected as always moving, and are replaced with information from a single input image, and the replacement of corrupted regions can be tailored to the scenario. We present our approach in the context of a panoramic tele-presence system. Tele-presence systems allow a user to experience a remote environment, aiming to create a realistic sense of "being there" and such a system should therefore provide a high quality visual rendition of the environment. Furthermore, panoramas, by virtue of capturing a greater proportion of a real-world scene, are often exposed to a greater dynamic range than standard photographs. Both facets of this system therefore stand to benefit from HDR imaging techniques. We demonstrate the success of our approach on multiple challenging ghosting scenarios, and compare our results with state-of-the-art methods previously proposed. We also demonstrate computational savings over these methods.

Cameras generally have a field of view only large enough to capture a portion of their surroundings. The goal of immersion is to replace many of your senses with virtual ones, so that the virtual environment will feel as real as possible. Panoramic cameras are used to capture the entire 360°view, also known as panoramic images.Virtual reality makes use of these panoramic images to provide a more immersive experience compared to seeing images on a 2D screen. This thesis, which is in the field of Computer vision, focuses on establishing a multi-camera geometry to generate a cylindrical panorama image and successfully implementing it with the cheapest cameras possible. The specific goal of this project is to propose the cameras geometry which will decrease artifact problems related to parallax in the panorama image. We present a new approach of cylindrical panoramic images from multiple cameras which its setup has cameras placed evenly around a circle. Instead of looking outward, which is the traditional ”radial” configuration, we propose to make the optical axes tangent to the camera circle, a ”tangential” configuration. Beside an analysis and comparison of radial and tangential geometries, we provide an experimental setup with real panoramas obtained in realistic conditions / Les caméras ont généralement un champ de vision à peine assez grand pour capturer partie de leur environnement. L’objectif de l’immersion est de remplacer virtuellement un grand nombre de sens, de sorte que l’environnement virtuel soit perçu comme le plus réel possible. Une caméra panoramique est utilisée pour capturer l’ensemble d’une vue 360°, également connue sous le nom d’image panoramique. La réalité virtuelle fait usage de ces images panoramiques pour fournir une expérience plus immersive par rapport aux images sur un écran 2D. Cette thèse, qui est dans le domaine de la vision par ordinateur, s’intéresse à la création d’une géométrie multi-caméras pour générer une image cylindrique panoramique et vise une mise en œuvre avec les caméras moins chères possibles. L’objectif spécifique de ce projet est de proposer une géométrie de caméra qui va diminuer au maximum les problèmes d’artefacts liés au parallaxe présent dans l’image panoramique. Nous présentons une nouvelle approche de capture des images panoramiques cylindriques à partir de plusieurs caméras disposées uniformément autour d’un cercle. Au lieu de regarder vers l’extérieur, ce qui est la configuration traditionnelle ”radiale”, nous proposons de rendre les axes optiques tangents au cercle des caméras, une configuration ”tangentielle”. Outre une analyse et la comparaison des géométries radiales et tangentielles, nous fournissons un montage expérimental avec de vrais panoramas obtenus dans des conditions réalistes