https://scholars.lib.ntu.edu.tw/handle/123456789/638434
標題: | Automated marker-free longitudinal infrared breast image registration by GA-PSO | 作者: | Lin, Fan Ya Lee, Chi En CHUNG-MING CHEN YEUN-CHUNG CHANG Huang, Chiun-Sheng |
關鍵字: | breast cancer | genetic algorithm | image registration | infrared image | particle swarm optimization | TPS | 公開日期: | 21-十二月-2023 | 卷: | 68 | 期: | 24 | 來源出版物: | Physics in Medicine and Biology | 摘要: | The automated marker-free longitudinal Infrared (IR) breast image registration overcomes several challenges like no anatomic fiducial markers on the body surface, blurry boundaries, heat pattern variation by environmental and physiological factors, nonrigid deformation, etc, has the ability of quantitative pixel-wise analysis with the heat energy and patterns change in a time course study. To achieve the goal, scale-invariant feature transform, Harris corner, and Hessian matrix were employed to generate the feature points as anatomic fiducial markers, and hybrid genetic algorithm and particle swarm optimization minimizing the matching errors was used to find the appropriate corresponding pairs between the 1st IR image and the nth IR image. Moreover, the mechanism of the IR spectrogram hardware system has a high level of reproducibility. The performance of the proposed longitudinal image registration system was evaluated by the simulated experiments and the clinical trial. In the simulated experiments, the mean difference of our system is 1.64 mm, which increases 57.58% accuracy than manual determination and makes a 17.4% improvement than the previous study. In the clinical trial, 80 patients were captured several times of IR breast images during chemotherapy. Most of them were well aligned in the spatiotemporal domain. In the few cases with evident heat pattern dissipation and spatial deviation, it still provided a reliable comparison of vascular variation. Therefore, the proposed system is accurate and robust, which could be considered as a reliable tool for longitudinal approaches to breast cancer diagnosis. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/638434 | ISSN: | 00319155 | DOI: | 10.1088/1361-6560/ad0357 |
顯示於: | 醫學工程學研究所 |
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