Automatic kidney segmentation from abdominal CT images is a key step in computer-aided diagnosis for kidney CT as well as computeraided surgery. However, kidney segmentation from CT images is generally performed manua...Automatic kidney segmentation from abdominal CT images is a key step in computer-aided diagnosis for kidney CT as well as computeraided surgery. However, kidney segmentation from CT images is generally performed manually or semi-autornatically because of gray levels similarities of adjacent organs/tissues in abdominal CT images. This paper presents an efficient algorithm for segmenting kidney from serials of abdominal CT images. First, we extracted estimated kidney position （EKP） according to the statistical geometric location of kidney within the abdomen. Second, we analyzed the intensity distribution of EKP for several abdominal CT images and exploit an adaptive threshold searching algorithm to eliminate many other organs/tissues in the EKP. Finally, a novel region growing approach based on labeling is used to obtain the fine kidney regions. Experimental results are comparable to those of manual tracing radiologist and shown to be efficient.展开更多
This letter presents an image orientation estimation method which is based on a combination of two techniques： quadrature filtering and nonlinear diffusion. The quadrature filters are used to get the orientation tens...This letter presents an image orientation estimation method which is based on a combination of two techniques： quadrature filtering and nonlinear diffusion. The quadrature filters are used to get the orientation tensors for edges, then the orientation tensors are smoothed through nonlinear diffusion. Experimental resuits and analysis show the robustness of the proposed method.展开更多
A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the s...A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process. Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.展开更多
This paper presented an object-based fast motion estimation (ME) algorithm for object-based texture coding in moving picture experts group four (MPEG-4), which takes full advantage of the shape information of video ob...This paper presented an object-based fast motion estimation (ME) algorithm for object-based texture coding in moving picture experts group four (MPEG-4), which takes full advantage of the shape information of video object. Compared with the full search (FS) algorithm, the proposed algorithm can significantly speed the ME process. The speed of ME using the proposed algorithm is faster than that using new three-step search (NTSS), four-step search (4SS), diamond search (DS), and block-based gradient descent search (BBGDS) algorithms with similar motion compensation (MC) errors. The proposed algorithm can be combined with other fast ME algorithm to make the ME process faster.展开更多
A new method of elastic articulated objects (human bodies) modeling was presented based on a new conic curve. The model includes 3D object deformable curves which can represent the deformation of human occluding conto...A new method of elastic articulated objects (human bodies) modeling was presented based on a new conic curve. The model includes 3D object deformable curves which can represent the deformation of human occluding contours. The deformation of human occluding contour can be represented by adjusting only four deformation parameters for each limb. Then, the 3D deformation parameters are determined by corresponding 2D contours from a sequence of stereo images. The algorithm presented in this paper includes deformable conic curve parameters determination and the plane, 3D conic curve lying on, parameter determination.展开更多
基金National Natural Science Foundations of China (No.60601025, No.60701022, No.30770561)
文摘Automatic kidney segmentation from abdominal CT images is a key step in computer-aided diagnosis for kidney CT as well as computeraided surgery. However, kidney segmentation from CT images is generally performed manually or semi-autornatically because of gray levels similarities of adjacent organs/tissues in abdominal CT images. This paper presents an efficient algorithm for segmenting kidney from serials of abdominal CT images. First, we extracted estimated kidney position （EKP） according to the statistical geometric location of kidney within the abdomen. Second, we analyzed the intensity distribution of EKP for several abdominal CT images and exploit an adaptive threshold searching algorithm to eliminate many other organs/tissues in the EKP. Finally, a novel region growing approach based on labeling is used to obtain the fine kidney regions. Experimental results are comparable to those of manual tracing radiologist and shown to be efficient.
文摘This letter presents an image orientation estimation method which is based on a combination of two techniques： quadrature filtering and nonlinear diffusion. The quadrature filters are used to get the orientation tensors for edges, then the orientation tensors are smoothed through nonlinear diffusion. Experimental resuits and analysis show the robustness of the proposed method.
基金Project (No. 2003CB716103) supported by the National BasicResearch Program (973) of China and the Key Lab for Image Proc-essing and Intelligent Control of National Education Ministry, China
文摘A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process. Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.
基金National High Technology Research and De-velopment Program of China (863 Program)(No.2003AA103810)
文摘This paper presented an object-based fast motion estimation (ME) algorithm for object-based texture coding in moving picture experts group four (MPEG-4), which takes full advantage of the shape information of video object. Compared with the full search (FS) algorithm, the proposed algorithm can significantly speed the ME process. The speed of ME using the proposed algorithm is faster than that using new three-step search (NTSS), four-step search (4SS), diamond search (DS), and block-based gradient descent search (BBGDS) algorithms with similar motion compensation (MC) errors. The proposed algorithm can be combined with other fast ME algorithm to make the ME process faster.
基金the Postdoctoral Science Foundation of China(Grant No.20070421018)
文摘A new method of elastic articulated objects (human bodies) modeling was presented based on a new conic curve. The model includes 3D object deformable curves which can represent the deformation of human occluding contours. The deformation of human occluding contour can be represented by adjusting only four deformation parameters for each limb. Then, the 3D deformation parameters are determined by corresponding 2D contours from a sequence of stereo images. The algorithm presented in this paper includes deformable conic curve parameters determination and the plane, 3D conic curve lying on, parameter determination.
