Short compute times are crucial for timely diagnostics in
biomedical applications, but lead to a high demand in computing for
new and improved imaging techniques. In this book reconfigurable
computing with FPGAs is discussed as an alternative to multi-core
processing and graphics card accelerators. Instead of adjusting the
application to the hardware, FPGAs allow the hardware to also be
adjusted to the problem. Acceleration of Biomedical Image
Processing with Dataflow on FPGAs covers the transformation of
image processing algorithms towards a system of deep pipelines that
can be executed with very high parallelism. The transformation
process is discussed from initial design decisions to working
implementations. Two example applications from stochastic
localization microscopy and electron tomography illustrate the
approach further. Topics discussed in the book include:*
Reconfigurable hardware* Dataflow computing* Image processing*
Application acceleration
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