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Three-dimensional (3D) (volumetric) diagnostic imaging techniques are indispensable with respect to the diagnosis and management of many medical conditions. However there is a lack of automated diagnosis techniques to facilitate such 3D image analysis (although some support tools do exist). This paper proposes a novel framework for volumetric medical image classification founded on homogeneous decomposition and dictionary learning. In the proposed framework each image (volume) is recursively decomposed until homogeneous regions are arrived at. Each region is represented using a Histogram of Oriented Gradients (HOG) which is transformed into a set of feature vectors. The Gaussian Mixture Model (GMM) is then used to generate a "dictionary" and the Improved Fisher Kernel (IFK) approach is used to encode feature vectors so as to generate a single feature vector for each volume, which can then be fed into a classifier generator. The principal advantage offered by the framework is that it does not require the detection (segmentation) of specific objects within the input data. The nature of the framework is fully described. A wide range of experiments was conducted with which to analyse the operation of the proposed framework and these are also reported fully in the paper. Although the proposed approach is generally applicable to 3D volumetric images, the focus for the work is 3D retinal Optical Coherence Tomography (OCT) images in the context of the diagnosis of Age-related Macular Degeneration (AMD). The results indicate that excellent diagnostic predictions can be produced using the proposed framework., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The development of a stable influenza subunit vaccine in the dry state was investigated. The influence of various carbohydrates, buffer types and freezing rates on the integrity of haemagglutinin after freeze-thawing or freeze-drying was investigated with a range of analytical and immunological methods. The use of fast freezing, Hepes buffer and carbohydrates (trehalose, inulin or dextran) as cryo- and lyoprotectants resulted in a significant reduction or even absence of conformational changes of HA as revealed by the used methods. The subunit vaccine in the powder was shown to remain immunogenic in an in vivo study in mice, using reconstituted powder. Moreover, the HA potency of the influenza subunit vaccine powder was stable for at least 26 weeks at room temperature.

In this study 27 full scale production batches of influenza sub-unit vaccine were evaluated on their stability. The batches varied with respect to the strains they contained and regarding the presence of the preservative thiomersal in the solution. The stability study showed that haemagglutinin content was the most sensitive parameter. An increase in the storage temperature strongly increased the degradation rate of haemagglutinin. The degradation rate of the haemagglutinin differed for the different strains tested. However, statistical evaluation of the data obtained for the most sensitive strain tested showed that even exposure during a 2 week period of the vaccine to room temperature would not adversely affect the shelf life claim of the influenza subunit vaccine of 1 year in the refrigerator. Moreover, this study showed that the presence of thiomersal in the solution has no effect on the stability of the vaccine.