Inventi Impact: Machine Vision
publication date: 2012/4/15

PERFORMANCE ANALYSIS OF MASSIVELY PARALLEL EMBEDDED HARDWARE ARCHITECTURES FOR RETINAL IMAGE PROCESSING
                  Alejandro Nieto, Victor Brea, David L Vilariño , Roberto R Osorio

ABSTRACT
This paper examines the implementation of a retinal vessel tree extraction technique on different hardware platforms and architectures. Retinal vessel tree extraction is a representative application of those found in the domain of medical image processing. The low signal-to-noise ratio of the images leads to a large amount of lowlevel tasks in order to meet the accuracy requirements. In some applications, this might compromise computing speed. This paper is focused on the assessment of the performance of a retinal vessel tree extraction method on different hardware platforms. In particular, the retinal vessel tree extraction method is mapped onto a massively parallel SIMD (MP-SIMD) chip, a massively parallel processor array (MPPA) and onto an field-programmable gate arrays (FPGA).

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