Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising

Scalable image data analysis is widely demanded in biomedical diagnosis by leveraging rapidly developed optical technology and advanced machine learning algorithm. However, bio-image obtained for single molecular or cell always have additive and multiplicative noise and requires denoising with b...

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Main Author:	Hu, Yifei
Other Authors:	Yu Hao
Format:	Theses and Dissertations
Language:	English
Published:	2017
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	http://hdl.handle.net/10356/72577
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-725772023-07-04T15:05:33Z Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising Hu, Yifei Yu Hao School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Scalable image data analysis is widely demanded in biomedical diagnosis by leveraging rapidly developed optical technology and advanced machine learning algorithm. However, bio-image obtained for single molecular or cell always have additive and multiplicative noise and requires denoising with better resolution in diagnosis. This dissertation proposed a high-throughput bioimage denoising method for different kinds of threedimensional microscopy cell images. Using a convolutional encoderdecoder network, one can provide a scalable bio-image platform, called NucleiNet, to automatically segment, classify and track cell nuclei. Using a benchmark of 2480 nuclei images, the experiment results show that the network achieves a 0.98 F-score and 0.99 pixel-wise accuracy, which means that over 95% of nuclei were successfully detected with no merging nuclei found. Key words: Image denoising, Convolutional neural network, Machine learning, Bio-image processing Master of Science (Electronics) 2017-08-29T04:12:30Z 2017-08-29T04:12:30Z 2017 Thesis http://hdl.handle.net/10356/72577 en 62 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering Hu, Yifei Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising
description	Scalable image data analysis is widely demanded in biomedical diagnosis by leveraging rapidly developed optical technology and advanced machine learning algorithm. However, bio-image obtained for single molecular or cell always have additive and multiplicative noise and requires denoising with better resolution in diagnosis. This dissertation proposed a high-throughput bioimage denoising method for different kinds of threedimensional microscopy cell images. Using a convolutional encoderdecoder network, one can provide a scalable bio-image platform, called NucleiNet, to automatically segment, classify and track cell nuclei. Using a benchmark of 2480 nuclei images, the experiment results show that the network achieves a 0.98 F-score and 0.99 pixel-wise accuracy, which means that over 95% of nuclei were successfully detected with no merging nuclei found. Key words: Image denoising, Convolutional neural network, Machine learning, Bio-image processing
author2	Yu Hao
author_facet	Yu Hao Hu, Yifei
format	Theses and Dissertations
author	Hu, Yifei
author_sort	Hu, Yifei
title	Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising
title_short	Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising
title_full	Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising
title_fullStr	Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising
title_full_unstemmed	Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising
title_sort	nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising
publishDate	2017
url	http://hdl.handle.net/10356/72577
_version_	1772827626591748096

Nucleinet: an encoder-decoder convolutional neural network for nuclei image denoising

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