Bio-Medical Materials and Engineering - Volume 24, issue 6

Authors: Gan, Hong-Seng | Tan, Tian-Swee | Wong, Liang-Xuan | Tham, Weng-Kit | Sayuti, Khairil Amir | Abdul Karim, Ahmad Helmy | bin Abdul Kadir, Mohammed Rafiq

Article Type: Research Article

Abstract: In medical image segmentation, manual segmentation is considered both labor- and time-intensive while automated segmentation often fails to segment anatomically intricate structure accordingly. Interactive segmentation can tackle shortcomings reported by previous segmentation approaches through user intervention. To better reflect user intention, development of suitable editing functions is critical. In this paper, we propose an interactive knee cartilage extraction software that covers three important features: intuitiveness, speed, and convenience. The segmentation is performed using multi-label random walks algorithm. Our segmentation software is simple to use, intuitive to normal and osteoarthritic image segmentation and efficient using only two third of manual segmentation's …time. Future works will extend this software to three dimensional segmentation and quantitative analysis. Show more

Keywords: Interactive segmentation, Knee cartilage, Magnetic resonance image, Random walks, User interface

DOI: 10.3233/BME-141137

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3145-3157, 2014

Authors: Liu, Hao | Zhao, Jianning | Dai, Ning | Qian, Hongbo | Tang, Yuehong

Article Type: Research Article

Abstract: Separation of the femur head and acetabulum is one of main difficulties in the diseased hip joint due to deformed shapes and extreme narrowness of the joint space. To improve the segmentation accuracy is the key point of existing automatic or semi-automatic segmentation methods. In this paper, we propose a new method to improve the accuracy of the segmented acetabulum using surface fitting techniques, which essentially consists of three parts: (1) design a surface iterative process to obtain an optimization surface; (2) change the ellipsoid fitting to two-phase quadric surface fitting; (3) bring in a normal matching method and an …optimization region method to capture edge points for the fitting quadric surface. Furthermore, this paper cited vivo CT data sets of 40 actual patients (with 79 hip joints). Test results for these clinical cases show that: (1) the average error of the quadric surface fitting method is 2.3 (mm); (2) the accuracy ratio of automatically recognized contours is larger than 89.4%; (3) the error ratio of section contours is less than 10% for acetabulums without severe malformation and less than 30% for acetabulums with severe malformation. Compared with similar methods, the accuracy of our method, which is applied in a software system, is significantly enhanced. Show more

Keywords: Acetabulum, segmentation, ellipsoid fitting, edge points, computer tomography

DOI: 10.3233/BME-141138

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3159-3177, 2014

Authors: Jia, Tong | Zhang, Hao | Meng, Haixiu

Article Type: Research Article

Abstract: Lung vessels often interfere with the detection of lung nodules. In this paper, a novel computer-aided lung nodule detection scheme on vessel segmentation is proposed. This paper describes an active contour model which can combine image region mean gray value and image edge energy. It is used to segment and remove lung vessels. A selective shape filter based on Hessian Matrix is used to detect suspicious nodules and remove omitted lung vessels. This paper extracts density, shape and position features of suspicious nodules, and uses a Rule-Based Classification (RBC) method to identify true positive nodules. In the experiment results, the …detection sensitivity is about 90% and FP is 1/scan. Show more

Keywords: Lung vessel segmentation, lung nodule detection, active contour model, CT image

DOI: 10.3233/BME-141139

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3179-3186, 2014

Authors: Mao, Yihao | Liu, Hong | Ye, Rong | Shi, Yonghong | Song, Zhijian

Article Type: Research Article

Abstract: Plaque assaying, measurement of the number, diameter, and area of plaques in a Petri dish image, is a standard procedure gauging the concentration of phage in biology. This paper presented a novel and effective method for implementing automatic plaque assaying. The method was mainly comprised of the following steps: In the training stage, after pre-processing the images for noise suppression, an initial training set was readied by sampling positive (with a plaque at the center) and negative (plaque-free) patches from the training images, and extracting the HOG features from each patch. The linear SVM classifier was trained in a self-learnt …supervised learning strategy to avoid possible missing detection. Specifically, the training set which contained positive and negative patches sampled manually from training images was used to train the preliminary classifier which exhaustively searched the training images to predict the label for the unlabeled patches. The mislabeled patches were evaluated by experts and relabeled. And all the newly labeled patches and their corresponding HOG features were added to the initial training set to train the final classifier. In the testing stage, a sliding-window technique was first applied to the unseen image for obtaining HOG features, which were inputted into the classifier to predict whether the patch was positive. Second, a locally adaptive Otsu method was performed on the positive patches to segment the plaques. Finally, after removing the outliers, the parameters of the plaques were measured in the segmented plaques. The experimental results demonstrated that the accuracy of the proposed method was similar to the one measured manually by experts, but it took less than 30 seconds. Show more

Keywords: Plaque assay, HOG, SVM, local adaptive image segmentation

DOI: 10.3233/BME-141140

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3187-3198, 2014

Authors: Wu, Huiqun | Geng, Xingyun | Zhang, Xiaofeng | Qiu, Mingyan | Jiang, Kui | Tang, Lemin | Dong, Jiancheng

Article Type: Research Article

Abstract: The optic disc (OD) is one of the important anatomic structures on the retina, the changes of which shape and area may indicate disease processes, thus needs computerized quantification assistance. In this study, we proposed a self-adaptive distance regularized level set evolution method for OD segmentation without the periodically re-initializing steps in the level set function execution to a signed distance function during the evolution. In that framework, preprocessing of an image was performed using Fourier correlation coefficient filtering to obtain initial boundary as the beginning contour, then, an accurate boundary of the optic disc was obtained using the self-adaptive …distance regularized level set evolution method. One hundred eye fundus color numerical images from public database were selected to validate our algorithm. Therefore, we believe that such automatic OD segmentation method could assist the ophthalmologist to segment OD more efficiently, which is of significance for future computer-aided early detection of glaucoma and retinopathy diseases. Show more

Keywords: Optic disk, retinal imaging, level set evolution, imaging informatics

DOI: 10.3233/BME-141141

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3199-3206, 2014

Authors: Li, Fang | Song, Zhijian

Article Type: Research Article

Abstract: Surface registration is widely used in image-guided neurosurgery to achieve spatial registration between the patient space and the image space. Coarse registration, followed by fine registration, is an important premise to ensure the robustness and efficiency of surface registration. In this paper, a coarse registration algorithm based on the principal axes is proposed to achieve this goal. The extraction of the principal axes relies on the approximated surface with an adaptive Gaussian kernel, the width of which is consistent with neighborhood relation so that it is applicable for various scanning data. Determining the corresponding centers of translation is another problem …for aligning different scanning data, which is solved through heuristics. Six pairs of points on two surfaces with the farthest projections on the principal axes were regarded as the candidates of translation centers, and then through tentative alignments of local regions around them, a pair of candidates with the minimum registration error was selected as the optimal translation centers. Automatic registration of two scans of a head phantom is presented in this paper. Experimental results confirmed the robustness of the algorithm and its feasibility in clinical applications. Show more

Keywords: Image-guided neurosurgery, coarse registration, principal axes, adaptive Gaussian kernel, heuristics

DOI: 10.3233/BME-141142

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3207-3214, 2014

Authors: Guo, Song | Luan, Fangjun | Song, Xiaoyu | Li, Changyou

Article Type: Research Article

Abstract: To better analyze images with the Gaussian white noise, it is necessary to remove the noise before image processing. In this paper, we propose a self-adaptive image denoising method based on bidimensional empirical mode decomposition (BEMD). Firstly, normal probability plot confirms that 2D-IMF of Gaussian white noise images decomposed by BEMD follow the normal distribution. Secondly, energy estimation equation of the ith 2D-IMF (i=2,3,4,......) is proposed referencing that of ith IMF (i=2,3,4,......) obtained by empirical mode decomposition (EMD). Thirdly, the self-adaptive threshold of each 2D-IMF is calculated. Eventually, the algorithm of the self-adaptive image denoising method based on BEMD is …described. From the practical perspective, this is applied for denoising of the magnetic resonance images (MRI) of the brain. And the results show it has a better denoising performance compared with other methods. Show more

Keywords: Image denoising, BEMD, self-adaption, Gaussian white noise, energy

DOI: 10.3233/BME-141143

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3215-3222, 2014

Authors: Geng, Lei | Shao, Yi-Ting | Xiao, Zhi-Tao | Zhang, Fang | Wu, Jun | Li, Min | Shan, Chun-Yan

Article Type: Research Article

Abstract: It has been demonstrated that shape, area and depth of the optic disc are relevant indices of diabetic retinopathy. In this paper, we present a new fundus optic disc localization and segmentation method based on phase congruency (PC). Firstly, in order to highlight the optic disc, channel images with the highest contrast between optic disc and background are selected in LAB, YUV, YIQ and HSV spaces respectively. Secondly, with the use of PC, features of four selected channel images can be extracted. Multiplication operation is then used to enhance PC detection results. Thirdly, window scanning and gray accumulating are utilized …to locate the optic disc. Finally, iterative OTSU automatic threshold segmentation and Hough transform are performed on location images, before the final optic disc segmentation result can be obtained. The experimental results showed that the proposed method can effectively and accurately perform optic disc location and segmentation. Show more

Keywords: Fundus image, phase congruency, optic disc localization, optic disc segmentation, diabetic retinopathy

DOI: 10.3233/BME-141144

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3223-3229, 2014

Authors: Cong, Jinyu | Wei, Benzheng | Yin, Yilong | Xi, Xiaoming | Zheng, Yuanjie

Article Type: Research Article

Abstract: Simple Linear Iterative Clustering (SLIC) algorithm is increasingly applied to different kinds of image processing because of its excellent perceptually meaningful characteristics. In order to better meet the needs of medical image processing and provide technical reference for SLIC on the application of medical image segmentation, two indicators of boundary accuracy and superpixel uniformity are introduced with other indicators to systematically analyze the performance of SLIC algorithm, compared with Normalized cuts and Turbopixels algorithm. The extensive experimental results show that SLIC is faster and less sensitive to the image type and the setting superpixel number than other similar algorithms such …as Turbopixels and Normalized cuts algorithms. And it also has a great benefit to the boundary recall, the robustness of fuzzy boundary, the setting superpixel size and the segmentation performance on medical image segmentation. Show more

Keywords: Medical image, superpixels, SLIC, image segmentation, performance evaluation

DOI: 10.3233/BME-141145

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3231-3238, 2014

Authors: Bian, Zijian | Tan, Wenjun | Yang, Jinzhu | Liu, Jiren | Zhao, Dazhe

Article Type: Research Article

Abstract: The quantitative analysis of the airway tree is of critical importance in the CT-based diagnosis and treatment of popular pulmonary diseases. The extraction of airway centerline is a precursor to identify airway hierarchical structure, measure geometrical parameters, and guide visualized detection. Traditional methods suffer from extra branches and circles due to incomplete segmentation results, which induce false analysis in applications. This paper proposed an automatic and robust centerline extraction method for airway tree. First, the centerline is located based on the topological thinning method; border voxels are deleted symmetrically to preserve topological and geometrical properties iteratively. Second, the structural information …is generated using graph-theoretic analysis. Then inaccurate circles are removed with a distance weighting strategy, and extra branches are pruned according to clinical anatomic knowledge. The centerline region without false appendices is eventually determined after the described phases. Experimental results show that the proposed method identifies more than 96% branches and keep consistency across different cases and achieves superior circle-free structure and centrality. Show more

Keywords: Airway tree, centerline extraction, topological thinning, graph-theoretic analysis

DOI: 10.3233/BME-141146

Citation: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 3239-3249, 2014