A novel endoscopic image analysis approach using deformable region model to aid in clinical diagnosis
A novel endoscopic image analysis approach using deformable region model to aid in clinical diagnosis
复制标题
一种利用可变形区域模型辅助临床诊断的新型内窥镜图像分析方法
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
M. Zheng
中科院分区：
文献类型：
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作者：
M. P. Tjoa;S. Krishnan;M. Zheng
提出了一种基于可变形区域模型的内窥镜图像分析方法。可变形区域模型方法通过最小交叉熵算法给出管腔的近似边界平面，然后自动将该平面变形到真实的边界，从而从内窥镜图像中确定管腔。边界变形采用生长收缩法。连通域标记法用于消除管腔外的小区域。该算法使用递归实现的草火概念。在倒置图像上应用连通域标记算法消除管腔内的小区域。随后，从管腔信息导出相关特征，可以检测内窥镜图像中的异常。所提出的计划已经过测试，使用一些内窥镜图像。所获得的结果支持所提出的方法的可行性，并具有极大的兴趣和潜在的诊断价值的临床医生。
A novel endoscopic image analysis approach using deformable region model has been proposed for clinical diagnosis. The deformable region model approach determines the lumen from the endoscopic image by giving an approximate boundary plan of the lumen by using minimum cross-entropy algorithm, and then deforming this plan to the real boundary automatically. A growing and shrinking method is employed for deforming the boundary. Connected components labeling method is used to eliminate small regions outside the lumen. The algorithm uses the grassfire concept implemented recursively. Applying connected components labeling algorithm on the inverted image eliminates small regions inside the lumen. Subsequently, deriving relevant features from the lumen information, abnormalities in the endoscopic image can be detected. The proposed scheme has been tested using a number of endoscopic images. The results obtained support the feasibility of the proposed approach and are of great interest and potential diagnostic value to the clinicians.