Publication:
Analysis of Motion Detection of Breast Tumor Based on Tissue Elasticity From B Mode Ultrasound Images Using Gradient Method Optical Flow Algorithm

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dc.ConferencecodeIEEE Malaysia Sect, IEEE Reg 8, Asia Modelling & Simulat Sect, UK Simulat Soc, European Simulat Council, European Council Modelling & Simulat, Univ Malaysia Sabah, Univ Malaysia Pahang, Univ Malaysia Perlis, Univ Technol Malaysia, Univ Technol Mara, Inst Technol Bandung, Univ Sci Malaysia, Machine Intelligence Res Labs, Nottingham Trent Univ, IEEE Comp Soc, Artificial Intelligence Res Unit
dc.ConferencedateDEC 03-05, 2013
dc.ConferencelocationKota Kinabalu, MALAYSIA
dc.Conferencename1st International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)
dc.contributor.authorShuib, FMMen_US
dc.contributor.authorMarinah Othmanen_US
dc.contributor.authorAbdulrahim, Ken_US
dc.contributor.authorZulkifli, Zen_US
dc.date.accessioned2024-05-29T02:50:36Z
dc.date.available2024-05-29T02:50:36Z
dc.date.issued2013
dc.descriptionDate of Conference: 03-05 December 2013 Conference Location: Kota Kinabalu, Malaysiaen_US
dc.description.abstractAs the effectiveness of an early detection of breast cancer using the mammography method alone is uncertain, it is crucial to provide an alternative method instead. This paper analyzes two optical flow algorithms utilizing a gradient method to aid current imaging techniques for a potential alternative method in aiding early breast cancer detection. The gradient method is a cost effective method that has the potential to be a mass screening method for this purpose. This paper compares two optical flow algorithms that are capable to detect the motion of breast tumor on B-mode ultrasound images. An analysis of 2D images of breast cancer lesions are compared using two gradient optical flow algorithms: Horn & Schunck and Lucas & Kanade. Both algorithms successfully show the direction of the tumor motion. However, while Lucas & Kanade can handle the short motion displacement of the tumor on the tested ultrasound images, Horn & Shunck failed to do so. This implies that the Lucas & Kanade algorithm is potentially more effective in handling ultrasound images of breast tumor. The results obtained showed that the Lucas&Kanade give better accuracy compared to Horn&Schunk.en_US
dc.identifier.citationF. M. M. Shuib, M. Othman, K. Abdulrahim and Z. Zulkifli, "Analysis of Motion Detection of Breast Tumor Based on Tissue Elasticity from B Mode Ultrasound Images Using Gradient Method Optical Flow Algorithm," 2013 1st International Conference on Artificial Intelligence, Modelling and Simulation, 2013, pp. 278-283, doi: 10.1109/AIMS.2013.51.en_US
dc.identifier.doi10.1109/AIMS.2013.51
dc.identifier.epage283
dc.identifier.scopusWOS:000358260900043
dc.identifier.spage278
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/11085
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.conference2013 First International Conference On Artificial Intelligence, Modelling And Simulation (Aims 2013)en_US
dc.sourceWeb Of Science (ISI)
dc.subjectoptical flow gradienten_US
dc.subjectelastrographyen_US
dc.subjectbreast canceren_US
dc.subjectultrasounden_US
dc.titleAnalysis of Motion Detection of Breast Tumor Based on Tissue Elasticity From B Mode Ultrasound Images Using Gradient Method Optical Flow Algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication

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