Siti Shufinaz, Mohd Zainudin (2004) Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin. Undergraduates thesis, University of Malaya.
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Abstract
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.
| Item Type: | Thesis ( Undergraduates) |
|---|---|
| Additional Information: | Academic Exercise (Bachelor’s Degree) – Faculty of Computer Science & Information Technology, University of Malaya, 2003/2004. |
| Uncontrolled Keywords: | Pulse-coupled neuron; Magnetic resonance image segmentation; Image smoothing; Image segmentation; Feature extraction |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Mr Mahadie Ab Latif |
| Date Deposited: | 24 May 2021 03:04 |
| Last Modified: | 24 May 2021 03:04 |
| URI: | http://studentsrepo.um.edu.my/id/eprint/10222 |
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