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Processing Extremely Large Images: Theory and Practice


Images encountered by today's scientist, with the advent of new hardware and methods in areas such as microscopy, synchrotron x-ray imaging, and satellite imaging, are a challenge to process within the common memory constraints and compute capabilities of a single CPU core. Through a resampling example, we provide an overview of the theory and modern practice of processing large images. By the end of this talk, attendees will understand how to develop and apply streaming methods. Furthermore, they will understand how to apply node-based and distributed parallelism to accelerate computation with SciPy tools such as NumPy, Dask, ITK, and the itk-jupyter-widgets.


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