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Performance analysis of massively parallel embedded hardware architectures for retinal image processing

Author(s): Nieto Alejandro | Brea Victor | VilariƱo David | Osorio Roberto

Journal: EURASIP Journal on Image and Video Processing
ISSN 1687-5176

Volume: 2011;
Issue: 1;
Start page: 10;
Date: 2011;
Original page

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 low-level 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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