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J. Imaging 2019, 5(1), 21; https://doi.org/10.3390/jimaging5010021

Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images

Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
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Received: 30 November 2018 / Revised: 27 December 2018 / Accepted: 11 January 2019 / Published: 17 January 2019
(This article belongs to the Special Issue Image Processing Using FPGAs)
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Abstract

Accurate and efficient detection of cell nuclei is an important step towards the development of a pathology-based Computer Aided Diagnosis. Generally, high-resolution histopathology images are very large, in the order of billion pixels, therefore nuclei detection is a highly compute intensive task, and software implementation requires a significant amount of processing time. To assist the doctors in real time, special hardware accelerators, which can reduce the processing time, are required. In this paper, we propose a Field Programmable Gate Array (FPGA) implementation of automated nuclei detection algorithm using generalized Laplacian of Gaussian filters. The experimental results show that the implemented architecture has the potential to provide a significant improvement in processing time without losing detection accuracy. View Full-Text
Keywords: FPGA implementation; hardware architecture; image processing; histopathology; generalized Laplacian of Gaussian filter; nuclei detection; mean Shift clustering FPGA implementation; hardware architecture; image processing; histopathology; generalized Laplacian of Gaussian filter; nuclei detection; mean Shift clustering
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Zhou, H.; Machupalli, R.; Mandal, M. Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images. J. Imaging 2019, 5, 21.

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