Wavelet Filter Parameterization for Compression of Spectral Images

Vaatimus kuvatiedon tiivistämisestä on tullut entistä ilmeisemmäksi viimeisen kymmenen vuoden aikana kuvatietoon perustuvien sovellutusten myötä. Nykyisin kiinnitetään erityistä huomiota spektrikuviin, joiden tallettaminen ja siirto vaativat runsaasti levytilaa ja kaistaa. Aallokemuunnos on osoittautunut hyväksi ratkaisuksi häviöllisessä tiedontiivistämisessä. Sen toteutus alikaistakoodauksessa perustuu aallokesuodattimiin ja ongelmana on sopivan aallokesuodattimen valinta erilaisille tiivistettäville kuville. Tässä työssä esitetään katsaus tiivistysmenetelmiin, jotka perustuvat aallokemuunnokseen. Ortogonaalisten suodattimien määritys parametrisoimalla on työn painopisteenä. Työssä todetaan myös kahden erilaisen lähestymistavan samanlaisuus algebrallisten yhtälöiden avulla. Kokeellinen osa sisältää joukon testejä, joilla perustellaan parametrisoinnin tarvetta. Erilaisille kuville tarvitaan erilaisia suodattimia sekä erilaiset tiivistyskertoimet saavutetaan eri suodattimilla. Lopuksi toteutetaan spektrikuvien tiivistys aallokemuunnoksen avulla.

Classification-Based compression of Multispectral Images

The purpose of this thesis is to present a new approach to the lossy compression of multispectral images. Proposed algorithm is based on combination of quantization and clustering. Clustering was investigated for compression of the spatial dimension and the vector quantization was applied for spectral dimension compression. Presenting algo¬rithms proposes to compress multispectral images in two stages. During the first stage we define the classes' etalons, another words to each uniform areas are located inside the image the number of class is given. And if there are the pixels are not yet assigned to some of the clusters then it doing during the second; pass and assign to the closest eta¬lons. Finally a compressed image is represented with a flat index image pointing to a codebook with etalons. The decompression stage is instant too. The proposed method described in this paper has been tested on different satellite multispectral images from different resources. The numerical results and illustrative examples of the method are represented too.

A phase IIa randomised clinical study of GNbAC1, a humanised monoclonal antibody against the envelope protein of multiple sclerosis-associated endogenous retrovirus in multiple sclerosis patients.

BACKGROUND: GNbAC1 is an immunoglobulin (IgG4) humanised monoclonal antibody against multiple sclerosis-associated retrovirus (MSRV)-Env, a protein of endogenous retroviral origin, expressed in multiple sclerosis (MS) lesions, which is pro-inflammatory and inhibits oligodendrocyte precursor cell differentiation. OBJECTIVE: This is a randomised, double-blind placebo-controlled dose-escalation study followed by a six-month open-label phase to test GNbAC1 in MS patients. The primary objective was to assess GNbAC1 safety in MS patients, and the other objectives were pharmacokinetic and pharmacodynamic assessments. METHODS: Ten MS patients were randomised into two cohorts to receive a single intravenous infusion of GNbAC1/placebo at doses of 2 or 6 mg/kg. Then all patients received five infusions of GNbAC1 at 2 or 6 mg/kg at four-week intervals in an open-label setting. Safety, brain magnetic resonance imaging (MRI), pharmacokinetics, immunogenicity, cytokines and MSRV RNA expression were studied. RESULTS: All patients completed the study. GNbAC1 was well tolerated in all patients. GNbAC1 pharmacokinetics is dose-linear with mean elimination half-life of 27-37 d. Anti-GNbAC1 antibodies were not detected. Cytokine analysis did not indicate an adverse effect. MSRV-transcripts showed a decline after the start of treatment. Nine patients had stable brain lesions at MRI. CONCLUSION: The safety, pharmacokinetic profile, and pharmacodynamic responses to GNbAC1 are favourable in MS patients over a six-month treatment period.

Statistical Analysis of Spectral Images

Tämä diplomityö liittyy Spektrikuvien tutkimiseen tilastollisen kuvamallin näkökulmasta. Diplomityön ensimmäisessä osassa tarkastellaan tilastollisten parametrien jakaumien vaikutusta väreihin ja korostumiin erilaisissa valaistusolosuhteissa. Havaittiin, että tilastollisten parametrien väliset suhteet eivät riipu valaistusolosuhteista, mutta riippuvat kuvan häiriöttömyydestä. Ilmeni myös, että korkea huipukkuus saattaa aiheutua värikylläisyydestä. Lisäksi työssä kehitettiin tilastolliseen spektrimalliin perustuvaa tekstuurinyhdistämisalgoritmia. Sillä saavutettiin hyviä tuloksia, kun tilastollisten parametrien väliset riippuvuussuhteet olivat voimassa. Työn toisessa osassa erilaisia spektrikuvia tutkittiin käyttäen itsenäistä komponenttien analyysia (ICA). Seuraavia itsenäiseen komponenttien analyysiin tarkoitettuja algoritmia tarkasteltiin: JADE, kiinteän pisteen ICA ja momenttikeskeinen ICA. Tutkimuksissa painotettiin erottelun laatua. Paras erottelu saavutettiin JADE- algoritmilla, joskin erot muiden algoritmien välillä eivät olleet merkittäviä. Algoritmi jakoi kuvan kahteen itsenäiseen, joko korostuneeseen ja korostumattomaan tai kromaattiseen ja akromaattiseen, komponenttiin. Lopuksi pohditaan huipukkuuden suhdetta kuvan ominaisuuksiin, kuten korostuneisuuteen ja värikylläisyyteen. Työn viimeisessä osassa ehdotetaan mahdollisia jatkotutkimuskohteita.

A phase IIa randomized clinical study testing GNbAC1, a humanized monoclonal antibody against the envelope protein of multiple sclerosis associated endogenous retrovirus in multiple sclerosis patients - A twelve month follow-up.

GNbAC1 is a humanized monoclonal antibody targeting MSRV-Env, an endogenous retroviral protein, which is expressed in multiple sclerosis (MS) lesions, is pro-inflammatory and inhibits oligodendrocyte precursor cell differentiation. This paper describes the open-label extension up to 12months of a trial testing GNbAC1 in 10 MS patients at 2 and 6mg/kg. The primary objective was to assess GNbAC1 safety, and other objectives were pharmacokinetic and pharmacodynamic assessments. During the extended study, no safety issues occurred in the 8 remaining patients. No anti-GNbAC1 antibodies were detected. GNbAC1 appears well tolerated.

Prediction of multiple infections after severe burn trauma: a prospective cohort study.

OBJECTIVE: To develop predictive models for early triage of burn patients based on hypersusceptibility to repeated infections. BACKGROUND: Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking. METHODS: Secondary analysis of 459 burn patients (≥16 years old) with 20% or more total body surface area burns recruited from 6 US burn centers. We compared blood transcriptomes with a 180-hour cutoff on the injury-to-transcriptome interval of 47 patients (≤1 infection episode) to those of 66 hypersusceptible patients [multiple (≥2) infection episodes (MIE)]. We used LASSO regression to select biomarkers and multivariate logistic regression to built models, accuracy of which were assessed by area under receiver operating characteristic curve (AUROC) and cross-validation. RESULTS: Three predictive models were developed using covariates of (1) clinical characteristics; (2) expression profiles of 14 genomic probes; (3) combining (1) and (2). The genomic and clinical models were highly predictive of MIE status [AUROCGenomic = 0.946 (95% CI: 0.906-0.986); AUROCClinical = 0.864 (CI: 0.794-0.933); AUROCGenomic/AUROCClinical P = 0.044]. Combined model has an increased AUROCCombined of 0.967 (CI: 0.940-0.993) compared with the individual models (AUROCCombined/AUROCClinical P = 0.0069). Hypersusceptible patients show early alterations in immune-related signaling pathways, epigenetic modulation, and chromatin remodeling. CONCLUSIONS: Early triage of burn patients more susceptible to infections can be made using clinical characteristics and/or genomic signatures. Genomic signature suggests new insights into the pathophysiology of hypersusceptibility to infection may lead to novel potential therapeutic or prophylactic targets.

Fatal Outcome of Multiple Clinical Presentations of Human Herpesvirus 8-related Disease After Solid Organ Transplantation.

Kaposi sarcoma is the most common human herpesvirus 8 (HHV-8)-related disease described after solid organ transplantation. Multicentric Castleman disease and hemophagocytic syndrome are other potential HHV-8-induced entities but are less frequently reported. We describe the case of a liver transplant recipient who presented with an acute febrile illness 1 year after transplantation with a rapidly fatal outcome. Autopsy revealed 3 distinct HHV-8-related entities: Kaposi sarcoma, HHV-8-associated multicentric Castleman disease with microlymphomas and a severe hemophagocytic syndrome. Retrospective serologic tests suggested that HHV-8 was likely transmitted by the seropositive donor at the time of transplantation. To our knowledge, this is the first case of copresentation of 3 clinical presentations of HHV-8-mediated human disease in the post-transplant setting. Considering the absence of systematic screening of organ donors/recipients for HHV-8 infection, HHV-8-related illness should be suspected in transplant recipients who present with acute febrile illness, systemic symptoms, lymphadenopathies, and/or multiorgan failure to rapidly document the diagnosis and provide timely an adequate treatment.

Feature-based matching of underwater images

This work investigates performance of recent feature-based matching techniques when applied to registration of underwater images. Matching methods are tested versus different contrast enhancing pre-processing of images. As a result of the performed experiments for various dominating in images underwater artifacts and present deformation, the outperforming preprocessing, detection and description methods are proposed

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.