Local feature fitting active contour for segmenting vessels in angiograms. Issue 3 (1st June 2014)

• Record Type: Journal Article
• Authors: Taghizadeh Dehkordi, Maryam; Doost Hoseini, Ali Mohamad; Sadri, Saeed; Soltanianzadeh, Hamid
• Is Part Of: IET computer vision. Volume 8:Issue 3(2014)
• Page Start: 161
• Page End: 170
• Publication Date: 2014-06-01
• Subjects: 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; Computer vision -- Periodicals; Pattern recognition systems -- Periodicals; 006.37
• DOI: 10.1049/iet-cvi.2013.0083
• Languages: English
• ISSNs: 1751-9632

Abstract

Abstract : 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.