Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin

The pulse-coupled neuron, which is significantly-different from the conventional artificial neuron, is a result of recent research conducted on the visual cortex of cats and monkeys. Pulse-coupled neural networks (PCNNs) are modeled to capture the essence of recent understanding of image interpretat...

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Main Author: Siti Shufinaz, Mohd Zainudin
Format: Thesis
Published: 2004
Subjects:
Online Access:http://studentsrepo.um.edu.my/10179/
http://studentsrepo.um.edu.my/10179/1/Siti_Shufinaz.pdf
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author Siti Shufinaz, Mohd Zainudin
author_facet Siti Shufinaz, Mohd Zainudin
author_sort Siti Shufinaz, Mohd Zainudin
building UM Research Repository
collection Online Access
description The pulse-coupled neuron, which is significantly-different from the conventional artificial neuron, is a result of recent research conducted on the visual cortex of cats and monkeys. Pulse-coupled neural networks (PCNNs) are modeled to capture the essence of recent understanding of image interpretation processes in biological neural systems. Study indicates that the PCNN is capable of image smoothing, image segmentation and feature extraction. The PCNN reduces noise in digital images better than traditional smoothing techniques. As an image segmented the PCNN performs well even when the intensity varies significantly within regions, and adjacent regions have overlapping intensity ranges.
first_indexed 2025-11-14T13:52:29Z
format Thesis
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institution University Malaya
institution_category Local University
last_indexed 2025-11-14T13:52:29Z
publishDate 2004
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repository_type Digital Repository
spelling um-101792021-06-30T01:18:02Z Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin Siti Shufinaz, Mohd Zainudin QA75 Electronic computers. Computer science QA76 Computer software The pulse-coupled neuron, which is significantly-different from the conventional artificial neuron, is a result of recent research conducted on the visual cortex of cats and monkeys. Pulse-coupled neural networks (PCNNs) are modeled to capture the essence of recent understanding of image interpretation processes in biological neural systems. Study indicates that the PCNN is capable of image smoothing, image segmentation and feature extraction. The PCNN reduces noise in digital images better than traditional smoothing techniques. As an image segmented the PCNN performs well even when the intensity varies significantly within regions, and adjacent regions have overlapping intensity ranges. 2004 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/10179/1/Siti_Shufinaz.pdf Siti Shufinaz, Mohd Zainudin (2004) Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin. Undergraduates thesis, University of Malaya. http://studentsrepo.um.edu.my/10179/
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Siti Shufinaz, Mohd Zainudin
Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin
title Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin
title_full Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin
title_fullStr Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin
title_full_unstemmed Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin
title_short Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin
title_sort magnetic resonance image segmentation using pulse-coupled neural network / siti shufinaz mohd zainudin
topic QA75 Electronic computers. Computer science
QA76 Computer software
url http://studentsrepo.um.edu.my/10179/
http://studentsrepo.um.edu.my/10179/1/Siti_Shufinaz.pdf