Automatic segmentation of vertebral contours from CT images using fuzzy corners. (1st May 2016)

• Record Type: Journal Article
• Authors: Athertya, Jiyo S.; Saravana Kumar, G.
• Is Part Of: Computers in biology and medicine. Volume 72(2016)
• Page Start: 75
• Page End: 89
• Publication Date: 2016-05-01
• Subjects: Medical image segmentation -- CT image -- Spine -- Active contour method -- Fuzzy logic -- Alpha hull; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2016.03.009
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Automatic segmentation of bone in computed tomography (CT) images is critical for the implementation of computer-assisted diagnosis which has increasing potential in the evaluation of various spine disorders. Of the many techniques available for delineating the region of interest (ROI), active contour methods (ACM) are well-established techniques that are used to segment medical images. The initialization for these methods is either through manual intervention or by applying a global threshold, thus making them semi-automatic in nature. The paper presents a methodology for automatic contour initialization in ACM and demonstrates the applicability of the method for medical image segmentation from spinal CT images. Initially, a set of feature markers from the image is extracted to construct an initial contour for the ACM. A fuzzified corner metric, based on image intensity, is proposed to identify the feature markers to be enclosed by the contour. A concave hull based on α shape, is constructed using these fuzzy corners to give the initial contour. The proposed method was evaluated against conventional feature detectors and other initialization methods. The results show the method׳s robust performance in the presence of simulated Gaussian noise levels. The method enables the ACM to efficiently converge to the ground truth segmentation. The reference standard for comparison was the annotated images from a radiologist, and the Dice coefficient and Hausdorff distance measures were used to evaluate the segmentation. Graphical abstract: Highlights: CT images of whole body spine is segmented using active contour method. Fully automated initialization method for active contour method is proposed. A novel fuzzy corner metric for identifying region of interest is employed. Automatic contour initialization using alpha hull constructed over detected fuzzy corners. Validation was done using the Dice coefficient and Hausdorff distance as compared to ground truth segmentation