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Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images

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,...

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Detalles Bibliográficos
Autores principales: Zhou, Haonan, Machupalli, Raju, Mandal, Mrinal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320863/
https://www.ncbi.nlm.nih.gov/pubmed/34465711
http://dx.doi.org/10.3390/jimaging5010021
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author Zhou, Haonan
Machupalli, Raju
Mandal, Mrinal
author_facet Zhou, Haonan
Machupalli, Raju
Mandal, Mrinal
author_sort Zhou, Haonan
collection PubMed
description 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.
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spelling pubmed-83208632021-08-26 Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images Zhou, Haonan Machupalli, Raju Mandal, Mrinal J Imaging Article 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. MDPI 2019-01-17 /pmc/articles/PMC8320863/ /pubmed/34465711 http://dx.doi.org/10.3390/jimaging5010021 Text en © 2019 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Zhou, Haonan
Machupalli, Raju
Mandal, Mrinal
Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images
title Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images
title_full Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images
title_fullStr Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images
title_full_unstemmed Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images
title_short Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images
title_sort efficient fpga implementation of automatic nuclei detection in histopathology images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320863/
https://www.ncbi.nlm.nih.gov/pubmed/34465711
http://dx.doi.org/10.3390/jimaging5010021
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