Shuib, FMMFMMShuibMarinah OthmanAbdulrahim, KKAbdulrahimZulkifli, ZZZulkifli2024-05-292024-05-292013F. 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.2013.51.10.1109/AIMS.2013.51WOS:000358260900043https://oarep.usim.edu.my/handle/123456789/11085Date of Conference: 03-05 December 2013 Conference Location: Kota Kinabalu, MalaysiaAs 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-USoptical flow gradientelastrographybreast cancerultrasoundArticle278283