Sparse non-negative matrix factorizations for ultrasound factor analysis |
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| Authors: | Xi Chen Kaizhi Wu Mingyue Ding Nong Sang |
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| Affiliation: | 1. Institute for Pattern Recognition and Artificial Intelligence, Science and Technology on Multi-spectral Information Processing Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China;2. Department of Biomedical Engineering, School of Life Science and Technology, Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan 430074, China;3. School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China |
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| Abstract: | Factor analysis is a powerful tool used for the analysis of dynamic studies. One of the major drawbacks of Factor Analysis of Dynamic Structures (FADS) is that the solution is not mathematically unique when only non-negativity constraints are used to determine factors and factor coefficients. In this paper, we introduce a novel method to correct FADS solutions by constructing and minimizing a new objective function. The method is improved from non-negative matrix factorizations (NMFs) algorithm by adding a sparse constraint that penalizes multiple components in the images of the factor coefficients. The technique is tested on computer simulations, and a patient ultrasound liver study. The results show that the method works well in comparison to the truth in computer simulations and to region of interest (ROI) measurements in the experimental studies. |
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| Keywords: | Dynamic ultrasound Factor analysis Sparse NMF |
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