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Conference Paper: Multi-resolution decomposition applied to crackle detection
Title | Multi-resolution decomposition applied to crackle detection |
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Authors | |
Keywords | Computers Cybernetics |
Issue Date | 1997 |
Publisher | IEEE. |
Citation | Computational Cybernetics and Simulation, IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings, Orlando, Florida, USA, 12-15 October 1997, v. 5, p. 4223-4226 How to Cite? |
Abstract | Crackles, heard over the lungs in a variety of diseases, are one of the most important physical signs in clinical medicine. They have an explosive pattern in the time domain, with a rapid onset and short duration. The timing, repeatability and shape of crackles are important parameters for diagnosis. Therefore, automatic detection of crackles and their classification as fine and coarse crackles have important clinical value. Since the multi-resolution decomposition technique can give high resolution in both time and frequency, it can be exploited to detect crackles and to classify them according to the information in each scale. In this paper, we present a new method for crackle detection based on the continuous wavelet transform. The theory, methods and experimental results are given in detail in this paper. |
Persistent Identifier | http://hdl.handle.net/10722/46043 |
ISSN | 2020 SCImago Journal Rankings: 0.168 |
DC Field | Value | Language |
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dc.contributor.author | Du, M | en_HK |
dc.contributor.author | Lam, FK | en_HK |
dc.contributor.author | Chan, FHY | en_HK |
dc.contributor.author | Sun, J | en_HK |
dc.date.accessioned | 2007-10-30T06:41:18Z | - |
dc.date.available | 2007-10-30T06:41:18Z | - |
dc.date.issued | 1997 | en_HK |
dc.identifier.citation | Computational Cybernetics and Simulation, IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings, Orlando, Florida, USA, 12-15 October 1997, v. 5, p. 4223-4226 | en_HK |
dc.identifier.issn | 1062-922X | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/46043 | - |
dc.description.abstract | Crackles, heard over the lungs in a variety of diseases, are one of the most important physical signs in clinical medicine. They have an explosive pattern in the time domain, with a rapid onset and short duration. The timing, repeatability and shape of crackles are important parameters for diagnosis. Therefore, automatic detection of crackles and their classification as fine and coarse crackles have important clinical value. Since the multi-resolution decomposition technique can give high resolution in both time and frequency, it can be exploited to detect crackles and to classify them according to the information in each scale. In this paper, we present a new method for crackle detection based on the continuous wavelet transform. The theory, methods and experimental results are given in detail in this paper. | en_HK |
dc.format.extent | 299851 bytes | - |
dc.format.extent | 13817 bytes | - |
dc.format.extent | 8841 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | text/plain | - |
dc.format.mimetype | text/plain | - |
dc.language | eng | en_HK |
dc.publisher | IEEE. | en_HK |
dc.rights | ©1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | Computers | en_HK |
dc.subject | Cybernetics | en_HK |
dc.title | Multi-resolution decomposition applied to crackle detection | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1062-922X&volume=5&spage=4223&epage=4226&date=1997&atitle=Multi-resolution+decomposition+applied+to+crackle+detection | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1109/ICSMC.1997.637362 | en_HK |
dc.identifier.hkuros | 34618 | - |
dc.identifier.issnl | 1062-922X | - |