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ABSTRACT: A computational framework is presented, based on statistical shape modelling, for construction of race-specific organ models for internal radionuclide dosimetry and other nuclear-medicine applications. This approach was applied to the construction of a Japanese liver phantom, using the liver of the digital Zubal phantom as the template and 35 liver computed tomography (CT) scans of male Japanese individuals as a training set. The first step was the automated object-space registration (to align all the liver surfaces in one orientation), using a coherent-point-drift maximum-likelihood alignment algorithm, of each CT scan-derived manually contoured liver surface and the template Zubal liver phantom. Six landmark points, corresponding to the intersection of the contours of the maximum-area sagittal, transaxial and coronal liver sections were employed to perform the above task. To find correspondence points in livers (i.e. 2000 points for each liver), each liver surface was transformed into a mesh, was mapped for the parameter space of a sphere (parameterisation), yielding spherical harmonics (SPHARMs) shape descriptors. The resulting spherical transforms were then registered by minimising the root-mean-square distance among the SPHARMs coefficients. A mean shape (i.e. liver) and its dispersion (i.e. covariance matrix) were next calculated and analysed by principal components. Leave-one-out-tests using 5-35 principal components (or modes) demonstrated the fidelity of the foregoing statistical analysis. Finally, a voxelisation algorithm and a point-based registration is utilised to convert the SPHARM surfaces into its corresponding voxelised and adjusted the Zubal phantom data, respectively. The proposed technique used to create the race-specific statistical phantom maintains anatomic realism and provides the statistical parameters for application to radionuclide dosimetry.
Radiation Protection Dosimetry 09/2010; 141(2):140-8. · 0.82 Impact Factor
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ABSTRACT: A computational framework is presented for 3-D liver shape approximation and characterization in order to determine the accuracy of shape reconstruction via Spherical Harmonics expansion. Spherical Harmonics is a powerful mathematical tool for expanding the shape. But in medical domain, livers have very variation geometry, in shape, size, and volume. In this regards, we evaluated and optimized the Spherical Harmonics to create 3-D parametric surface of the liver from Computed Tomography (CT) imaging system which may useful for Shape modeling, surface representation, physical measurement of objects and mathematical model. We select randomly 5 livers from more 100 dataset. Mean Hausdorff distance Errors and Dice similarity coefficient DSC by liver volumes was measured. The experimental results showed that the best order of Spherical Harmonics Expansion for livers is between 12~17.
Intelligent Information Hiding and Multimedia Signal Processing, International Conference on. 09/2009;
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ABSTRACT: This paper describes procedures for repositioning calculations of fractured bone fragments using 3-D-computed tomography (CT), aimed at preoperative planning for computer-guided fracture reduction of the proximal femur. Fracture boundaries of the bone fragments, as "fracture lines (FLs)," and the mirror-transformed contralateral femur shape extracted from 3-D-CT were used for repositioning of the fragments. We first describe a method for extracting FLs based on 3-D curvature analysis and then formulate repositioning methods based on registration of bone fragments using the following three constraints: 1) contralateral (CL) femur shape; 2) FLs; and 3) both CL femur shape and fracture lines, as "both constraints". We performed experiments using CT datasets from five simulated and four real patients with proximal femoral fracture. We evaluated the rotation error in reposition calculations and the contact ratio between repositioned fragment boundaries, which are crucial for the recovery of proper functional axes and bone adhesion of fragments, respectively. Experimental results showed that good accuracy and stability were attainable when registration using both constraints was performed after registration using the fracture-line constraint. On average, 6.0 degrees +/-0.8 degrees in rotation error and 89%+/-3 % in contact ratio were obtained without providing precise initial values.
IEEE transactions on bio-medical engineering 04/2009; 56(3):749-59. · 2.15 Impact Factor
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Fifth International Conference on Natural Computation, ICNC 2009, Tianjian, China, 14-16 August 2009, 6 Volumes; 01/2009
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Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2009), Kyoto, Japan, 12-14 September, 2009, Proceedings; 01/2009
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Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2009), Kyoto, Japan, 12-14 September, 2009, Proceedings; 01/2009
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Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2009), Kyoto, Japan, 12-14 September, 2009, Proceedings; 01/2009
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ABSTRACT: An atlas-based automated liver segmentation method from three-dimensional computed tomographic (3D CT) images has been developed. The method uses two types of atlases, a probabilistic atlas (PA) and a statistical shape model (SSM).
Voxel-based segmentation with a PA is first performed to obtain a liver region, then the obtained region is used as the initial region for subsequent SSM fitting to 3D CT images. To improve reconstruction accuracy, particularly for highly deformed livers, we use a multilevel SSM (ML-SSM). In ML-SSM, the entire shape is divided into patches, with principal component analysis applied to each patch. To avoid inconsistency among patches, we introduce a new constraint called the "adhesiveness constraint" for overlapping regions among patches.
The PA and ML-SSM were constructed from 20 training datasets. We applied the proposed method to eight evaluation datasets. On average, volumetric overlap of 89.2 +/- 1.4% and average distance of 1.36 +/- 0.19 mm were obtained.
The proposed method was shown to improve segmentation accuracy for datasets including highly deformed livers. We demonstrated that segmentation accuracy is improved using the initial region obtained with PA and the introduced constraint for ML-SSM.
Academic radiology 12/2008; 15(11):1390-403. · 2.09 Impact Factor
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ABSTRACT: An atlas-based automated liver segmentation method from 3D CT images is described. The method utilizes two types of atlases, that is, the probabilistic atlas (PA) and statistical shape model (SSM). Voxel-based segmentation with PA is firstly performed to obtain a liver region, and then the obtained region is used as the initial region for subsequent SSM fitting to 3D CT images. To improve reconstruction accuracy especially for largely deformed livers, we utilize a multi-level SSM (ML-SSM). In ML-SSM, the whole shape is divided into patches, and principal component analysis is applied to each patches. To avoid the inconsistency among patches, we introduce a new constraint called the adhesiveness constraint for overlap regions among patches. In experiments, we demonstrate that segmentation accuracy improved by using the initial region obtained with PA and the introduced constraint for ML-SSM.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 02/2007; 10(Pt 1):86-93.
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ABSTRACT: We show in this paper a feasibility of self organization of loop neural circuit for memory, association, and abstraction, which is algorithmically realizable. First we assume the memory is composed of loop neural circuit in the cerebral cortex. Then, we give how a memory content expressed by loop circuit shape is copied to blank area of cerebral cortex as well as how a path between memory loops with the same shape is found by broadcasting based on the classical Hebbian law. The generated sequence from the transmitting loop corresponding to the memory is a code by pseudo random sequence which is now popular in spread spectrum communication or mobile CDMA. Further, we show how the association and abstraction of the memory can be realized by the neural circuit. The loop circuit self-organizing model seems to be reasonable in the sense of hardware realizable, having large number of codes corresponding to various memory contents, and able to access to other memories associatively. Thus, the model seems able to account well unifiedly the information processing function of the brain.
Intelligent Information Hiding and Multimedia Signal Processing, International Conference on.
