Bio-Medical Materials and Engineering - Volume 26, issue s1

Authors: Wang, Rui | Zhou, Yongquan | Zhao, Chengyan | Wu, Haizhou

Article Type: Research Article

Abstract: Multi-threshold image segmentation is a powerful image processing technique that is used for the preprocessing of pattern recognition and computer vision. However, traditional multilevel thresholding methods are computationally expensive because they involve exhaustively searching the optimal thresholds to optimize the objective functions. To overcome this drawback, this paper proposes a flower pollination algorithm with a randomized location modification. The proposed algorithm is used to find optimal threshold values for maximizing Otsu’s objective functions with regard to eight medical grayscale images. When benchmarked against other state-of-the-art evolutionary algorithms, the new algorithm proves itself to be robust and effective through numerical experimental …results including Otsu’s objective values and standard deviations. Show more

Keywords: Flower pollination algorithm, randomized location, Otsu method, multi-threshold image segmentation, medical image segmentation

DOI: 10.3233/BME-151432

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1345-S1351, 2015

Authors: Hu, Liang | Cheng, Zhaoning | Wang, Manning | Song, Zhijian

Article Type: Research Article

Abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used for breast lesion differentiation. Manual segmentation in DCE-MRI is difficult and open to viewer interpretation. In this paper, an automatic segmentation method based on image manifold revealing was introduced to overcome the problems of the currently used method. First, high dimensional datasets were constructed from a dynamic image series. Next, an embedded image manifold was revealed in the feature image by nonlinear dimensionality reduction technique. In the last stage, k-means clustering was performed to obtain final segmentation results. The proposed method was applied in actual clinical cases and compared with the …gold standard. Statistical analysis showed that the proposed method achieved an acceptable accuracy, sensitivity, and specificity rates. Show more

Keywords: Breast lesion, manifold learning, DCE-MRI, tumor segmentation, dimensionality reduction

DOI: 10.3233/BME-151433

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1353-S1360, 2015

Authors: Le, Trong-Ngoc | Bao, Pham The | Huynh, Hieu Trung

Article Type: Research Article

Abstract: In this paper, a fully automatic scheme for measuring liver volume in 3D MR images was developed. The proposed MRI liver volumetry scheme consisted of four main stages. First, the preprocessing stage was applied to T1-weighted MR images of the liver in the portal-venous phase to reduce noise. The histogram of the 3D image was determined, and the second-to-last peak of the histogram was calculated using a neural network. Thresholds, which are determined based upon the second-to-last peak, were used to generate a thresholding image. This thresholding image was refined using a gradient magnitude image. The morphological and connected component …operations were applied to the refined image to generate the rough shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the rough shape in order to more precisely determine the liver boundaries. The liver volumes determined by the proposed automatic volumetry were compared to those manually traced by radiologists; these manual volumes were used as a “gold standard.” The two volumetric methods reached an excellent agreement. The Dice overlap coefficient and the average accuracy were 91.0 ±2.8% and 99.0 ±0.4%, respectively. The mean processing time for the proposed automatic scheme was 1.02 ±0.08 min (CPU: Intel, core i7, 2.8GHz), whereas that of the manual volumetry was 24.3 ±3.7 min (p < 0.001). Show more

Keywords: Liver volumetry, MR volumetry, resection, transplantation, magnetic resonance imaging

DOI: 10.3233/BME-151434

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1361-S1369, 2015

Authors: Huang, Po-Chia | Hsu, Ching-Han

Article Type: Research Article

Abstract: Pinhole SPECT for small animal has become a routine procedure in many applications of molecular biology and pharmaceutical development. There is an increasing demand in the whole body imaging of lab animals. A simple and direct solution is to scan the object along a helical trajectory, similar to a helical CT scan. The corresponding acquisition time can be greatly reduced, while the over-lapping and gap between consecutive bed positions can be avoided. However, helical pinhole SPECT inevitably leads to the tremendous increase in computational complexity when the iterative reconstruction algorithms are applied. We suggest a novel voxel-driven (VD) system model …which can be integrated with geometric symmetries from helical trajectory for fast iterative image reconstruction. Such a model construction can also achieve faster calculation and lower storage requirement of the system matrix. Due to the independence among various symmetries, it permits parallel coding to further boost computation efficiency of forward/backward projection. From phantom study, the results also indicate that the proposed VD model can adequately model the helical pinhole SPECT scanner with manageable storage size of system matrix and clinically acceptable computation loading of reconstruction. Show more

Keywords: Pinhole SPECT, helical trajectory, voxel-driven system model, ray-tracing algorithms

DOI: 10.3233/BME-151435

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1371-S1380, 2015

Authors: Liu, Ruigang | Fu, Feng | You, Fusheng | Shi, Xuetao | Dong, Xiuzhen

Article Type: Research Article

Abstract: Static imaging of the electrical impedance tomography can obtain the absolute electrical conductivity distribution at one section of the subject. The test is performed on a cylinder physical phantom in which slim rectangle, hollow cylinder, small rectangle or three cylinders are selected to simulate complex conductivity perturbation objects. The measurement data is obtained by a data acquisition system with 32 compound electrodes. A group of static images of conductivity distribution in the cylinder phantom are reconstructed by the modified Newton-Raphson algorithm with two kinds of regularization methods. The results show correct position, size, conductivity difference, and similar shape of the …perturbation objects in the images. Show more

Keywords: Electrical impedance, tomography, reconstruction algorithm, physical phantom, static imaging

DOI: 10.3233/BME-151436

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1381-S1388, 2015

Authors: Qi, Hongliang | Chen, Zijia | Guo, Jingyu | Zhou, Linghong

Article Type: Research Article

Abstract: Low-dose computed tomography reconstruction is an important issue in the medical imaging domain. Sparse-view has been widely studied as a potential strategy. Compressed sensing (CS) method has shown great potential to reconstruct high-quality CT images from sparse-view projection data. Nonetheless, low-contrast structures tend to be blurred by the total variation (TV, L1 -norm of the gradient image) regularization. Moreover, TV will produce blocky effects on smooth and edge regions. To overcome this limitation, this study has proposed an iterative image reconstruction algorithm by combining L1 regularization and smoothed L0 (SL0 ) regularization. SL0 is a smooth approximation …of L0 norm and can solve the problem of L0 norm being sensitive to noise. To evaluate the proposed method, both qualitative and quantitative studies were conducted on a digital Shepp-Logan phantom and a real head phantom. Experimental comparative results have indicated that the proposed L1 /SL0 -POCS algorithm can effectively suppress noise and artifacts, as well as preserve more structural information compared to other existing methods. Show more

Keywords: Sparse-view reconstruction, smoothed L0 regularization, L1 regularization, total variation

DOI: 10.3233/BME-151437

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1389-S1398, 2015

Authors: Sajjad, Muhammad | Mehmood, Irfan | Baik, Sung Wook

Article Type: Research Article

Abstract: Image super-resolution (SR) plays a vital role in medical imaging that allows a more efficient and effective diagnosis process. Usually, diagnosing is difficult and inaccurate from low-resolution (LR) and noisy images. Resolution enhancement through conventional interpolation methods strongly affects the precision of consequent processing steps, such as segmentation and registration. Therefore, we propose an efficient sparse coded image SR reconstruction technique using a trained dictionary. We apply a simple and efficient regularized version of orthogonal matching pursuit (ROMP) to seek the coefficients of sparse representation. ROMP has the transparency and greediness of OMP and the robustness of the L 1 …-minization that enhance the dictionary learning process to capture feature descriptors such as oriented edges and contours from complex images like brain MRIs. The sparse coding part of the K-SVD dictionary training procedure is modified by substituting OMP with ROMP. The dictionary update stage allows simultaneously updating an arbitrary number of atoms and vectors of sparse coefficients. In SR reconstruction, ROMP is used to determine the vector of sparse coefficients for the underlying patch. The recovered representations are then applied to the trained dictionary, and finally, an optimization leads to high-resolution output of high-quality. Experimental results demonstrate that the super-resolution reconstruction quality of the proposed scheme is comparatively better than other state-of-the-art schemes. Show more

Keywords: Image super-resolution, sparse representations, reconstruction, dictionary

DOI: 10.3233/BME-151438

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1399-S1407, 2015

Authors: Zhou, Ziying | Li, Yugang | Zhang, Fa | Wan, Xiaohua

Article Type: Research Article

Abstract: Electron tomography (ET) is an essential imaging technique for studying structures of large biological specimens. These structures are reconstructed from a set of projections obtained at different sample orientations by tilting the specimen. However, most of existing reconstruction methods are not appropriate when the data are extremely noisy and incomplete. A new iterative method has been proposed: adaptive simultaneous algebraic reconstruction with inter-iteration adaptive non-linear anisotropic diffusion (NAD) filter (FASART). We also adopted an adaptive parameter and discussed the step for the filter in this reconstruction method. Experimental results show that FASART can restrain the noise generated in the process …of iterative reconstruction and still preserve the more details of the structure edges. Show more

Keywords: electron tomography (ET), 3D reconstruction, iterative method, non-linear anisotropic diffusion (NAD) filter

DOI: 10.3233/BME-151439

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1409-S1415, 2015

Authors: Lee, Sangyong | Chin, Seongah

Article Type: Research Article

Abstract: Recently, advanced visualizing techniques in computer graphics have considerably enhanced the visual appearance of synthetic models. To realize enhanced visual graphics for synthetic medical effects, the first step followed by rendering techniques involves attaching albedo textures to the region where a certain graphic is to be rendered. For instance, in order to render wound textures efficiently, the first step is to recognize the area where the user wants to attach a wound. However, in general, face indices are not stored in sequential order, which makes sub-texturing difficult. In this paper, we present a novel mesh tagging algorithm that utilizes a …task for mesh traversals and level extension in the general case of a wound sub-texture mapping and a selected region deformation in a three-dimensional (3D) model. This method works automatically on both regular and irregular mesh surfaces. The approach consists of mesh selection (MS), mesh leveling (ML), and mesh tagging (MT). To validate our approach, we performed experiments for synthesizing wounds on a 3D face model and on a simulated mesh. Show more

Keywords: Wound synthesis, medical image synthesis, irregular mesh, regular mesh, mesh indexing

DOI: 10.3233/BME-151440

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1417-S1429, 2015

Authors: Jao, Jochi | Cheng, Mingye | Lee, Hsintien | Ting, Julius | Chen, Pochou

Article Type: Research Article

Abstract: Magnetic Resonance Imaging (MRI) has been one of the most revolutionary medical imaging modalities in the past three decades. It has been recognized as a potential technique in the clinical diagnosis of diseases as well as tumor differentiation. Although MRI has now become the preferred choice in many clinical examinations, there are some drawbacks, which still limit its applications. One of the crucial issues of MRI is the geometric distortion caused by magnetic field inhomogeneity and susceptibility effects. The farther the lesion from the center of a magnetic field (off-center field), the more severe the distortion becomes, especially in low-field …MRI. Hence, it might hinder the diagnosis and characterization of lesions in the presence of field inhomogeneity. In this study, an innovative multi-orientated water-phantom was used to evaluate the geometric distortion. The correlations between the level of image distortion and the relative off-center positions, as well as the variation of signal intensities, were both investigated. The image distortion ratios of axial, coronal and sagittal images were calculated. Show more

Keywords: Geometric distortion, field inhomogeneity, off-center field, multi-orientated water-phantom

DOI: 10.3233/BME-151441

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1431-S1438, 2015