| MEDICAL IMAGE SEGMENTATION BASED ON A MODIFIED LEVEL SET ALGORITHM |
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| 作者姓名： | 杨勇 林盘 郑崇勋 顾建文 |
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| 作者单位： | Key Laboratory of Biomedical Information Engineering of Education Ministry，Institute of Biomedical Engineering，Xi'an Jiaotong University，Xi'an 710049，China，Key Laboratory of Biomedical Information Engineering of Education Ministry，Institute of Biomedical Engineering，Xi'an Jiaotong University，Xi'an 710049，China，Key Laboratory of Biomedical Information Engineering of Education Ministry，Institute of Biomedical Engineering，Xi'an Jiaotong University，Xi'an 710049，China，Key Laboratory of Biomedical Information Engineering of Education Ministry，Institute of Biomedical Engineering，Xi'an Jiaotong University，Xi'an 710049，China |
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| 基金项目： | ThisresearchwassupportedbytheNationalNaturalScienceFoundationofChina(No.30000224and30000056) |
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| 摘 要： | Imagesegmentationplaysanimportantrolein imageanalysisaswellasinhigh levelimageinter pretationandunderstandingsuchasrobotvision, objectrecognition,andmedicalimaging.Numerous segmentationmethodshavebeendeveloped.How ever,medicalimagesareoftencorruptedbyno…
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| 关 键 词： | 医学图像分割 水平集 速度方程 区域信息 |
MEDICAL IMAGE SEGMENTATION BASED ON A MODIFIED LEVEL SET ALGORITHM |
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| Yang Yong,LIN Pan,Zheng Chongxun,GU Jianwen.MEDICAL IMAGE SEGMENTATION BASED ON A MODIFIED LEVEL SET ALGORITHM[J].Academic Journal of Xi’an Jiaotong University,2005,17(1):29-32,56. |
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| Authors: | Yang Yong LIN Pan Zheng Chongxun GU Jianwen |
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| Institution: | Key Laboratory of Biomedical Information Engineering of Education Ministry, Institute of Biomedical Engineering, Xi'an Jiaotong University, Xi'an 710049,China |
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| Abstract: | Objective To present a novel modified level set algorithm for medical image segmentation. Methods The algorithm is developed by substituting the speed function of level set algorithm with the region and gradient information of the image instead of the conventional gradient information. This new algorithm has been tested by a series of different modality medical images. Results We present various examples and also evaluate and compare the performance of our method with the classical level set method on weak boundaries and noisy images. Conclusion Experimental results show the proposed algorithm is effective and robust. |
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| Keywords: | medical image segmentation level set speed function region information |
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