Biomedical image processing and reconstruction with dataflow computing on FPGAs

Author

Grull, Frederik ; Kebschull, Udo

Author_Institution

IRI, Goethe Univ. Frankfurt, Frankfurt am Main, Germany

fYear

2014

fDate

2-4 Sept. 2014

Firstpage

1

Lastpage

2

Abstract

Increasing chip sizes and better programming tools have made it possible to increase the boundaries of application acceleration with FPGAs. Two applications, localization microscopy and electron tomography, are presented in the author´s PhD thesis and summarized in this paper. Both have been ported from imperative languages to the dataflow paradigm that maps well onto long processing pipelines in custom hardware. The results show that an acceleration of 200 compared to an Intel i5 450 CPU for localization microscopy, and an acceleration of 5 over an Nvidia Tesla C1060 for electron tomography while maintaining full accuracy. The main challenge arose from the need to fully understand and re-write most of the imperative source in a form suitable for dataflow computing.

Keywords

computerised tomography; data flow computing; field programmable gate arrays; image reconstruction; medical image processing; microscopy; FPGA; Intel i5 450 CPU; Nvidia Tesla C1060; biomedical image processing; biomedical image reconstruction; central processing unit; dataflow computing; dataflow paradigm; electron tomography; field programmable gate array; imperative languages; localization microscopy; Acceleration; Electron microscopy; Field programmable gate arrays; Optical microscopy; Pipelines; Tomography;

fLanguage

English

Publisher

ieee

Conference_Titel

Field Programmable Logic and Applications (FPL), 2014 24th International Conference on

Conference_Location

Munich

Type

conf

DOI

10.1109/FPL.2014.6927378

Filename

6927378