Local feature fitting active contour for segmenting vessels in angiograms

被引:25
作者
Dehkordi, Maryam Taghizadeh [1 ]
Hoseini, Ali Mohamad Doost [1 ]
Sadri, Saeed [1 ]
Soltanianzadeh, Hamid [2 ]
机构
[1] Isfahan Univ Technol, Elect & Comp Engn Dept, Esfahan 841568311, Iran
[2] Univ Tehran, Sch Elect & Comp Engn, Tehran 14395515, Iran
关键词
blood vessels; diagnostic radiography; feature extraction; Hessian matrices; image segmentation; medical image processing; coronary X-ray angiogram; synthetic image; image intensity inhomogeneity; local region intensity information; pixel-vessel structure correspondence degree; filter output; directional Hessian-based framework; vesselness filter; local feature fitting energy function; vascular segmentation; active contour model accuracy; vessel segmentation; local feature fitting active contour; SEGMENTATION; EXTRACTION; MODEL;
D O I
10.1049/iet-cvi.2013.0083
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An active contour model for vascular segmentation has been proposed, by defining a new, local, feature fitting, energy function. A vesselness filter is applied to the image in a directional Hessian-based framework. The filter output, as a feature, expresses the degree of the correspondence of each pixel to the vessel structure. By using intensity information obtained from local regions, the proposed model is able to solve the problem of intensity inhomogeneity in images. In addition, by introducing this feature into the fitting process, the model exhibits greater accuracy when compared to existing models. Experimental results from synthetic images and coronary X-ray angiograms verify the desirable performance of the proposed model.
引用
收藏
页码:161 / 170
页数:10
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