Cardiovascular instrumentation for spaceflight

The observation mechanisms dealing with pressure, flow, morphology, temperature, etc. are discussed. The approach taken in the performance of this study was to (1) review ground and space-flight data on cardiovascular function, including earlier related ground-based and space-flight animal studies, Mercury, Gemini, Apollo, Skylab, and recent bed-rest studies, (2) review cardiovascular measurement parameters required to assess individual performance and physiological alternations during space flight, (3) perform an instrumentation survey including a literature search as well as personal contact with the applicable investigators, (4) assess instrumentation applicability with respect to the established criteria, and (5) recommend future research and development activity. It is concluded that, for the most part, the required instrumentation technology is available but that mission-peculiar criteria will require modifications to adapt the applicable instrumentation to a space-flight configuration

Probabilistic partial volume modelling of biomedical tomographic image data

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Quantified phenotype analysis in a cell model for Autosomal Dominant Retinitis Pigmentosa

Modern cell biology relies greatly on microscopy to assess distribution and dynamics of fluorescently labelled cellular proteins. Quantified image analysis allows not only measurement of clear differences between individual phenotypes and time points, but also discovery of subtle changes which are not obvious to an observer by visual inspection. In this dissertation, we quantitatively characterise wild type and mutations P23H/A/L in rhodopsin in a cellular model for autosomal dominant retinitis pigmentosa in stable HEK 293S cell lines and in GMK cells. Autosomal dominant retinitis pigmentosa is a genetic disorder which can lead to photoreceptor cell death and result in reduced vision and complete blindness. Endoplasmic Reticulum chaperone calnexin was also quantified from both immune-labelled fixed cells, and from transient co-transfection of live cells. The clinically relevant severity of rhodopsin mutations was in keeping with the phenotypes of the cellular model. The severe mutation P23H showed the lowest volume of rhodopsin-GFP in both cell lines in comparison to wild-type. We also reported a significantly higher calnexin volume in HEK293 and GMK expressing P23H rhodopsin (with p<0.05). Less severe mutants had a phenotype more similar to wildtype. Colocalisation was assessed using a simple approach of overlapping volume. As co-expression of rhodopsin and calnexin during time-lapse acquisition induced cytotoxicity and accelerated cellular death, we assessed phototoxicity caused by blue light illumination. We quantified motility and division rates in PC3 and GMK mammalian cell cultures, respectively. A surprisingly low phototoxicity threshold of 13.9 J/cm2 was determined for imaging unlabelled GMK cells without inducing mitotic delay. To assess the production of reactive oxygen species, which are key to phototoxicity in fluorescence microscopy, the end-product hydrogen peroxide was monitored using a ratiometric biosensor. Finally, all findings are synthesised as practical guidelines for end users

Optimisation of image processing networks for neuronal membrane detection

This research dealt with the problem of neuronal membrane detection, in which the core challenge is distinguishing membranes from organelles. A simple and efficient optimisation framework is proposed based on several basic processing steps, including local contrast enhancement, denoising, thresholding, hole-filling, watershed segmentation, and morphological operations. The two main algorithms proposed Image Processing Chain Optimisation (IPCO) and Multiple IPCO (MIPCO)combine elements of Genetic Algorithms, Differential Evolution, and Rank-based uniform crossover. 91.67% is the highest recorded individual IPCO score with a speed of 280 s, and 92.11% is the highest recorded ensembles IPCO score whereas 91.80% is the highest recorded individual MIPCO score with a speed of 540 s for typically less than 500 optimisation generations and 92.63% is the highest recorded ensembles MIPCO score.Further, IPCO chains and MIPCO networks do not require specialised hardware and they are easy to use and deploy. This is the first application of this approach in the context of the Drosophila first instar larva ventral nerve cord. Both algorithms use existing image processing functions, but optimise the way in which they are configured and combined. The approach differs from related work in terms of the set of functions used, the parameterisations allowed, the optimisation methods adopted, the combination framework, and the testing and analyses conducted. Both IPCO and MIPCO are efficient and interpretable, and facilitate the generation of new insights. Systematic analyses of the statistics of optimised chains were conducted using 30 microscopy slices with corresponding ground truth. This process revealed several interesting and unconventional insights pertaining to preprocessing, classification, post-processing, and speed, and the appearance of functions in unorthodox positions in image processing chains, suggesting new sets of pipelines for image processing. One such insight revealed that, at least in the context of our membrane detection data, it is typically better to enhance, and even classify, data before denoising them

Optimisation of image processing networks for neuronal membrane detection

This research dealt with the problem of neuronal membrane detection, in which the core challenge is distinguishing membranes from organelles. A simple and efficient optimisation framework is proposed based on several basic processing steps, including local contrast enhancement, denoising, thresholding, hole-filling, watershed segmentation, and morphological operations. The two main algorithms proposed Image Processing Chain Optimisation (IPCO) and Multiple IPCO (MIPCO)combine elements of Genetic Algorithms, Differential Evolution, and Rank-based uniform crossover. 91.67% is the highest recorded individual IPCO score with a speed of 280 s, and 92.11% is the highest recorded ensembles IPCO score whereas 91.80% is the highest recorded individual MIPCO score with a speed of 540 s for typically less than 500 optimisation generations and 92.63% is the highest recorded ensembles MIPCO score.Further, IPCO chains and MIPCO networks do not require specialised hardware and they are easy to use and deploy. This is the first application of this approach in the context of the Drosophila first instar larva ventral nerve cord. Both algorithms use existing image processing functions, but optimise the way in which they are configured and combined. The approach differs from related work in terms of the set of functions used, the parameterisations allowed, the optimisation methods adopted, the combination framework, and the testing and analyses conducted. Both IPCO and MIPCO are efficient and interpretable, and facilitate the generation of new insights. Systematic analyses of the statistics of optimised chains were conducted using 30 microscopy slices with corresponding ground truth. This process revealed several interesting and unconventional insights pertaining to preprocessing, classification, post-processing, and speed, and the appearance of functions in unorthodox positions in image processing chains, suggesting new sets of pipelines for image processing. One such insight revealed that, at least in the context of our membrane detection data, it is typically better to enhance, and even classify, data before denoising them