433 research outputs found

    Quick Annotator: an open-source digital pathology based rapid image annotation tool.

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    Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest is laborious and often intractable even in moderately sized cohorts. Here, we present an open-source tool, Quick Annotator (QA), designed to improve annotation efficiency of histologic structures by orders of magnitude. While the user annotates regions of interest (ROIs) via an intuitive web interface, a deep learning (DL) model is concurrently optimized using these annotations and applied to the ROI. The user iteratively reviews DL results to either (1) accept accurately annotated regions or (2) correct erroneously segmented structures to improve subsequent model suggestions, before transitioning to other ROIs. We demonstrate the effectiveness of QA over comparable manual efforts via three use cases. These include annotating (1) 337,386 nuclei in 5 pancreatic WSIs, (2) 5,692 tubules in 10 colorectal WSIs, and (3) 14,187 regions of epithelium in 10 breast WSIs. Efficiency gains in terms of annotations per second of 102×, 9×, and 39× were, respectively, witnessed while retaining f-scores >0.95, suggesting that QA may be a valuable tool for efficiently fully annotating WSIs employed in downstream biomarker studies

    Successful transition from fed-batch to continuous manufacturing within a mAb process development cycle

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    Centrifuge Modelling of Earthquake Effects in Uniform Deposits of Saturated Sand

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    Centrifuge models representing level uniform saturated deposits of relatively loose and dense sand were tested at Cambridge University\u27s Schofield Centre to clarify the behaviour of these deposits under earthquake loading. The excess pore pressure, vertical propagation of the accelerations and ground surface settlements resulting from a model earthquake are presented and discussed. The results show that, for similar dynamic loading, the models undergo large shear stiffness degradation resulting from significant pore pressure build up, this taking place at a slower rate in the dense sand. As a result of the cyclic loading, the models suffer settlements, occurring mostly during the event, that are noticeably smaller in the dense model. The upwards propagation of the accelerations through the model depends on the relative density of the sand and changes during the seismic event, following degradation of sand mechanical properties. Large short-duration acceleration spikes are observed near the surface of the dense model, corresponding to large amplification of input acceleration. The results presented and discussed contribute to the understanding of the basic mechanisms of earthquake-induced liquefaction and the use of densification as a measure to mitigate its effects
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