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Performance evaluation of spot detection algorithms in fluorescence microscopy images

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dc.contributor.author Mabaso, M
dc.contributor.author Twala, B
dc.contributor.author Withey, Daniel J
dc.contributor.author Utete, S
dc.date.accessioned 2012-10-31T13:05:11Z
dc.date.available 2012-10-31T13:05:11Z
dc.date.issued 2012-10
dc.identifier.citation Mabaso, M, Twala, B, Withey, D.J. and Utete, S. Performance evaluation of spot detection algorithms in fluorescence microscopy images. 4th CSIR Biennial Conference: Real problems relevant solutions, CSIR, Pretoria, 9-10 October 2012 en_US
dc.identifier.uri http://hdl.handle.net/10204/6257
dc.description 4th CSIR Biennial Conference: Real problems relevant solutions, CSIR, Pretoria, 9-10 October 2012 en_US
dc.description.abstract Detection of messenger Ribonucleic Acid (mRNA) spots in fluorescence microscopy images is of great importance for biologists seeking better understanding of cell functionality. Fluorescence microscopy and specific staining methods make biological molecules appear as bright spots in image data. Manual analysis of such data is both time-consuming and laborious, and can lead to errors. In this study, we compare two computer-based detection methods used in fluorescence microscopy images for the detection of spots. The algorithms compared are the Isotropic Undecimated Wavelet Transform (IUWT) and the Feature Particle Detection (FPD). The performance of these algorithms is validated on synthetic images. Our study finds a major difference in the performance of the two algorithms. IUWT performs better than FPD. en_US
dc.language.iso en en_US
dc.subject Fluorescence microscopy en_US
dc.subject mRNA en_US
dc.subject messenger Ribonucleic Acid en_US
dc.subject Isotropic Undecimated Wavelet Transform en_US
dc.subject IUWT en_US
dc.subject Feature Particle Detection en_US
dc.subject FPD en_US
dc.subject Algorithms en_US
dc.subject Particle detection en_US
dc.subject Noise en_US
dc.title Performance evaluation of spot detection algorithms in fluorescence microscopy images en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Mabaso, M., Twala, B., Withey, D. J., & Utete, S. (2012). Performance evaluation of spot detection algorithms in fluorescence microscopy images. http://hdl.handle.net/10204/6257 en_ZA
dc.identifier.chicagocitation Mabaso, M, B Twala, Daniel J Withey, and S Utete. "Performance evaluation of spot detection algorithms in fluorescence microscopy images." (2012): http://hdl.handle.net/10204/6257 en_ZA
dc.identifier.vancouvercitation Mabaso M, Twala B, Withey DJ, Utete S, Performance evaluation of spot detection algorithms in fluorescence microscopy images; 2012. http://hdl.handle.net/10204/6257 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Mabaso, M AU - Twala, B AU - Withey, Daniel J AU - Utete, S AB - Detection of messenger Ribonucleic Acid (mRNA) spots in fluorescence microscopy images is of great importance for biologists seeking better understanding of cell functionality. Fluorescence microscopy and specific staining methods make biological molecules appear as bright spots in image data. Manual analysis of such data is both time-consuming and laborious, and can lead to errors. In this study, we compare two computer-based detection methods used in fluorescence microscopy images for the detection of spots. The algorithms compared are the Isotropic Undecimated Wavelet Transform (IUWT) and the Feature Particle Detection (FPD). The performance of these algorithms is validated on synthetic images. Our study finds a major difference in the performance of the two algorithms. IUWT performs better than FPD. DA - 2012-10 DB - ResearchSpace DP - CSIR KW - Fluorescence microscopy KW - mRNA KW - messenger Ribonucleic Acid KW - Isotropic Undecimated Wavelet Transform KW - IUWT KW - Feature Particle Detection KW - FPD KW - Algorithms KW - Particle detection KW - Noise LK - https://researchspace.csir.co.za PY - 2012 T1 - Performance evaluation of spot detection algorithms in fluorescence microscopy images TI - Performance evaluation of spot detection algorithms in fluorescence microscopy images UR - http://hdl.handle.net/10204/6257 ER - en_ZA


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